Tackling Environmental Justice with One Backpack
Libraries Needed
library(factoextra)## Warning: package 'factoextra' was built under R version 4.3.3## Loading required package: ggplot2## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBalibrary(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(data.table)##
## Attaching package: 'data.table'## The following objects are masked from 'package:dplyr':
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## between, first, lastlibrary(ggplot2)
library(maps)## Warning: package 'maps' was built under R version 4.3.3Loading & Subsetting Data
#EJI Data
eji = read.csv("C:/Users/Katie/Desktop/EJI.csv")
eji_ny = eji[which(eji$StateDesc == 'New York'),]
eji_ny = eji_ny[which(eji_ny$COUNTY == 'New York' | eji_ny$COUNTY == "Bronx" | eji_ny$COUNTY == "Kings" | eji_ny$COUNTY == "Queens"), ]#PM2.5 Data
pops_2.5_walk1 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk1.csv") #ny
pops_2.5_walk1$walk = 1
pops_2.5_walk2 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk2.csv") #ny
pops_2.5_walk2$walk = 2
pops_2.5_walk3 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk3.csv") #ny
pops_2.5_walk3$walk = 3
pops_2.5_walk4 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk4.csv") #ny
pops_2.5_walk4$walk = 4
pops_2.5_walk5 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk5.csv") #ny
pops_2.5_walk5$walk = 5
pops_2.5_walk6 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk6.csv") #ny
pops_2.5_walk6$walk = 6
pops_2.5_walk7 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk7.csv") #ny
pops_2.5_walk7$walk = 7
pops_2.5_walk8 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk8.csv") #ny
pops_2.5_walk8$walk = 8
pops_2.5_walk9 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk9.csv") #ny/kings
pops_2.5_walk9$walk = 9
pops_2.5_walk10 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk10.csv") #ny
pops_2.5_walk10$walk = 10
pops_2.5_walk11 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk11.csv") #ny
pops_2.5_walk11$walk = 11
pops_2.5_walk12 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk12.csv") #ny
pops_2.5_walk12$walk = 12
pops_2.5_walk13 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk13.csv") #ny
pops_2.5_walk13$walk = 13
pops_2.5_walk14 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk14.csv") #ny
pops_2.5_walk14$walk = 14
pops_2.5_walk15 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk15.csv") #ny
pops_2.5_walk15$walk = 15
pops_2.5_walk16 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk16.csv") #kings
pops_2.5_walk16$walk = 16
pops_2.5_walk17 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk17.csv") #kings
pops_2.5_walk17$walk = 17
pops_2.5_walk18 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk18.csv") #ny/bronx
pops_2.5_walk18$walk = 18
pops_2.5_walk19 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk19.csv") #ny/bronx
pops_2.5_walk19$walk = 19
pops_2.5_walk20 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk20.csv") #ny/bronx
pops_2.5_walk20$walk = 20
pops_2.5_walk21 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk21.csv") #ny
pops_2.5_walk21$walk = 21
pops_2.5_walk22 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk22.csv") #ny
pops_2.5_walk22$walk = 22
pops_2.5_walk23 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk23.csv") #ny
pops_2.5_walk23$walk = 23
pops_2.5_walk24 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk24.csv") #ny
pops_2.5_walk24$walk = 24
pops_2.5_walk25 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk25.csv") #ny
pops_2.5_walk25$walk = 25
pops_2.5_walk26 = read.csv("C:/Users/Katie/Desktop/NYC_POPS_DATA/NYC_POPS_PAM_pm1_pm25_walk26.csv") #ny
pops_2.5_walk26$walk = 26
pops_2.5_allwalks = rbind(pops_2.5_walk1,pops_2.5_walk2, pops_2.5_walk3, pops_2.5_walk4, pops_2.5_walk5, pops_2.5_walk6, pops_2.5_walk7, pops_2.5_walk8, pops_2.5_walk9, pops_2.5_walk10, pops_2.5_walk11, pops_2.5_walk12, pops_2.5_walk13, pops_2.5_walk14, pops_2.5_walk15, pops_2.5_walk16, pops_2.5_walk17, pops_2.5_walk18, pops_2.5_walk19, pops_2.5_walk20, pops_2.5_walk21, pops_2.5_walk22, pops_2.5_walk23, pops_2.5_walk24, pops_2.5_walk25, pops_2.5_walk26)
allwalks = pops_2.5_allwalks[which(pops_2.5_allwalks$TimeUTC != "NaT"), ]
allwalks$COUNTY = ifelse(allwalks$walk >= 1 & allwalks$walk <= 15, "New York",
ifelse(allwalks$walk >= 16 & allwalks$walk <= 17, "Kings",
ifelse(allwalks$walk >= 18 & allwalks$walk <= 26, "New York", "Pending")))
allwalks[5535:5831, 13] = "Kings" #walk 9
allwalks[11584:11681, 13] = "Bronx" #walk 18
allwalks[11897:12215, 13] = "Bronx" #walk 19
allwalks[12392:12829, 13] = "Bronx" #walk 20
allwalks_base = allwalks %>%
select(TimeUTC, PM25_POPS, walk, COUNTY)Variables of Interest
Name of Census Tract
E_TOTPOP # estimated total population from 2014-2018
E_OZONE # annual mean days above O3 regulatory standard (3-year average)
E_PM # annual mean days above PM2.5 regulatory standards (3-year average)
E_PARK #proportion of census tract’s area within 1 mi buffer of green space
E_AIRPORT #proportion of census tract’s area within 1 mi buffer of airport
E_TOTCR #probability of contracting cancer over the course of a lifetime assuming continous exposure
RPL_EJI # EJI rank
RPL_EBM # environmental burden rank
RPL_SVM # social vulnerability module rank
RPL_HVM # percentile rank of combined tertile (health risks) flags
EP_MINRTY # percentage of minority persons
EP_POV200 # percentage below 200% poverty
EP_CANCER # percentage of individuals with cancer
EP_ASTHMA # percentage of individuals with asthma
EP_LIMENG # percentage of persons (5+) who speak English “less than well”
EP_DISABL # percentage of persons who are disabled
EP_AGE65 # percentage of persons aged 65 and older
EP_UNINSUR # percentage or persons uninsured
EP_UNEMP # percentage of persons with no high school diploma (25+)
Base Model
- Name of Census Tract (index column)
- E_PM # annual mean days above PM2.5 regulatory standards (3-year average)
- E_TOTCR # probability of contracting cancer over the course of a lifetime assuming continuous exposure
- EP_MINRTY # percentage of minority persons
- RPL_EJI # EJI rank
- RPL_SVM # social vulnerability module rank
- E_TOTPOP # estimated total population from 2014-2018
Base Model
Exploratory Analysis
EJI Box Plots & Summary Statistics
#Base Model Variables
eji_base = eji_ny %>%
select(NAME, COUNTY, E_PM, E_TOTCR, EP_MINRTY, RPL_EJI, RPL_SVM, E_TOTPOP)
#Summary Statistics
eji_base %>%
group_by(COUNTY) %>%
summarise(median_min = median(EP_MINRTY), mean_min = mean(EP_MINRTY))#Categorizing majority "minority" counties
#This is based on the average % of minorities in each county
eji_base$minority = ifelse(eji_base$EP_MINRTY >= 87 & eji_base$COUNTY == "Bronx", "minority",
ifelse(eji_base$EP_MINRTY >= 62 & eji_base$COUNTY == "Kings", "minority",
ifelse(eji_base$EP_MINRTY >= 51 & eji_base$COUNTY == "New York", "minority",
ifelse(eji_base$EP_MINRTY >= 72 & eji_base$COUNTY == "Queens", "minority", "non-minority"))))
#Box plot of NY Counties and Rank of EJI
#Minority counties def have a higher EJI rank than non-minority counties
#New York county has the biggest disparity
ggplot(eji_base, aes(x= COUNTY, y=RPL_EJI, fill = minority)) +
geom_boxplot() +
coord_flip() +
scale_fill_manual(values = c("darkseagreen", "burlywood3")) +
#geom_jitter(position = position_jitter(0.15)) +
theme_classic() +
labs(x = "New York Counties", y = "Rank of EJI")## Warning: Removed 59 rows containing non-finite values (`stat_boxplot()`).
#Box plot of NY counties vs Above Pm2.5 Regulatory Standards
#There is not a substantial difference between minority and non-minority counties.
#Queens does have the largest spread.
ggplot(eji_base, aes(x= COUNTY, y=E_PM, fill = minority)) +
geom_boxplot() +
coord_flip() +
scale_fill_manual(values = c("darkseagreen", "burlywood3")) +
#geom_jitter(position = position_jitter(0.15)) +
theme_classic() +
labs(x = "New York Counties", y = "Annaul Mean Days Above PM2.5 Regulatory Standards")## Warning: Removed 2 rows containing non-finite values (`stat_boxplot()`).
#Box plot of NY counties vs Social Vulnerability Rank
#Minority counties have a higher social vulnerability rank than non-minority counties
#Kings and Queens have the largest spread
#New York has the biggest difference between non-minority and minortiy counties
ggplot(eji_base, aes(x= COUNTY, y=RPL_SVM, fill = minority)) +
geom_boxplot() +
coord_flip() +
scale_fill_manual(values = c("darkseagreen", "burlywood3")) +
#geom_jitter(position = position_jitter(0.15)) +
theme_classic() +
labs(x = "New York Counties", y = "Social Vulnerability Rank")## Warning: Removed 50 rows containing non-finite values (`stat_boxplot()`).
Histograms of CDC vs Backpack Campaign
CDC
#Loading in CDC estimated daily concentration levels for PM2.5
#Am only using 2016 - Aug and July - for a direct comparison to Backpack campaign
#Also only looking at the four new york counties of interest
#EJI uses these predicted values from 2014-2016
CDC_PM25 = read.csv("C:/Users/Katie/Desktop/CDC Daily Concentration Levels.csv")
CDC_PM25_sub = CDC_PM25[which((CDC_PM25$countyfips == 5 | CDC_PM25$countyfips == 61 | CDC_PM25$countyfips == 47 | CDC_PM25$countyfips == 81) & CDC_PM25$year == 2016), ]
#Renaming the counties
CDC_PM25_sub$county = ifelse(CDC_PM25_sub$countyfips == 5, "Bronx",
ifelse(CDC_PM25_sub$countyfips == 47, "Kings",
ifelse(CDC_PM25_sub$countyfips == 61, "New York", "Queens")))
#Changing county variable to factor
CDC_PM25_sub$county = as.factor(CDC_PM25_sub$county)
#Histogram of CDC estimated PM2.5 for these coutnies
#For July & Aug of 2016 the range for the daily PM2.5 is about 0 to 20 for each county
ggplot(CDC_PM25_sub, aes(x=PM25_pop_pred, fill = county)) +
geom_histogram( color="#e9ecef", alpha=0.6, position = 'identity') +
facet_wrap(~county) +
xlab("Predicted PM2.5 Concentration Levels") +
ylab("Frequency of PM2.5 Levels")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
summary(CDC_PM25_sub$PM25_pop_pred)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.209 6.899 9.065 9.258 11.195 17.481#Min = 3.209, #Median = 9.065, #Max = 17.481Backpacking Campaign
#Creating a day variable from the TimeUTC var.
#Removing some outliers for more easy comparison
allwalks_base$day = sub("^\\d+/([0-9]+)/\\d+.*", "\\1", allwalks_base$TimeUTC)
allwalks_base = allwalks_base[which(allwalks_base$PM25_POPS <= 150), ]
#Histogram of Backpacking PM2.5 by county
#This is not an average by the PM2.5 seen every 15 minutes for each walk
#The range here is much higher than CDC.
#We are seeing much higher levels of PM2.5
ggplot(allwalks_base, aes(x=PM25_POPS, fill = COUNTY)) +
geom_histogram( color="#e9ecef", alpha=0.6, position = 'identity') +
facet_wrap(~COUNTY) +
xlab("Backpack Campaign Concentration Levels") +
ylab("Frequency of PM2.5 Levels")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#Averaging the PM2.5 by day
allwalks_base_grouped = allwalks_base %>%
group_by(day, COUNTY) %>%
summarise(PM25_avg = mean(PM25_POPS, na.rm = TRUE))## `summarise()` has grouped output by 'day'. You can override using the `.groups`
## argument.#Histogram of the backpacking campaign of the average PM2.5 per day by county
#Still averaging it shows that there are higher reading for PM2.5 compared to CDC predicted
ggplot(allwalks_base_grouped, aes(x=PM25_avg, fill = COUNTY)) +
geom_histogram(color="#e9ecef", alpha=0.6, position = 'identity') +
facet_wrap(~COUNTY) +
xlab("Backpack Campaign Concentration Levels") +
ylab("Frequency of PM2.5 Levels")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
summary(allwalks_base$PM25_POPS)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.382 9.117 15.733 19.295 28.898 148.109#Min = 1.382, Median = 15.778, #3rd Quartile = 29.050 #Max = 423Bronx clustering analysis
Base Model
Training Data
eji_base_bronx = eji_base[which(eji_base$COUNTY == 'Bronx'),]
eji_base_bronx = na.omit(eji_base_bronx)
#Finding what variables to use from base model
library(caret)## Warning: package 'caret' was built under R version 4.3.3## Loading required package: latticecorrelation_matrix = cor(eji_base_bronx[, c(3:8)]) #EP_MINRTY, RPL_SVM, RPL_EJI
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_base_bronx)), size = 231)
train = eji_base_bronx[train_sample, ]
test = eji_base_bronx[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 61.5%
kmeans_result ## K-means clustering with 2 clusters of sizes 189, 42
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 0.3914532 0.368285 0.3479536
## 2 -1.7615394 -1.657283 -1.5657912
##
## Clustering vector:
## 42807 42638 42823 42935 42745 42928 42858 42873 42959 42780 42715 42716 42885
## 1 1 2 1 1 1 1 1 1 1 2 1 1
## 42825 42949 42764 42650 42631 42944 42883 42839 42703 42706 42667 42770 42656
## 1 2 1 1 1 1 1 2 1 1 1 1 1
## 42736 42892 42647 42762 42853 42793 42845 42919 42694 42697 42701 42688 42768
## 1 1 1 1 2 1 2 1 1 2 1 1 1
## 42838 42951 42906 42665 42950 42852 42640 42743 42719 42891 42864 42711 42663
## 2 2 1 1 2 1 1 1 1 1 1 2 1
## 42786 42869 42837 42658 42627 42637 42925 42872 42714 42649 42907 42748 42737
## 1 2 2 1 1 1 1 1 1 1 1 1 2
## 42785 42689 42827 42692 42778 42710 42792 42763 42675 42699 42806 42733 42865
## 1 2 2 1 1 1 1 1 1 2 2 1 2
## 42724 42948 42842 42754 42832 42840 42801 42641 42818 42670 42678 42790 42861
## 1 1 1 1 2 2 1 1 1 1 1 1 2
## 42895 42912 42704 42648 42740 42843 42734 42930 42849 42835 42890 42781 42729
## 1 1 1 1 1 2 1 1 2 2 1 1 1
## 42787 42918 42782 42797 42628 42695 42914 42882 42934 42645 42679 42700 42791
## 1 1 1 2 1 1 1 1 1 1 1 1 1
## 42708 42908 42871 42941 42932 42672 42702 42841 42812 42738 42876 42824 42624
## 1 1 1 1 1 1 2 2 2 1 1 1 1
## 42795 42654 42867 42848 42713 42939 42804 42644 42731 42718 42879 42676 42735
## 1 1 2 2 1 1 2 1 1 1 1 2 1
## 42646 42805 42666 42683 42709 42635 42896 42887 42900 42889 42933 42862 42859
## 1 1 1 1 1 1 1 1 1 1 1 1 2
## 42875 42799 42855 42660 42769 42947 42752 42657 42664 42634 42828 42633 42942
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 42854 42685 42779 42922 42958 42954 42943 42794 42742 42888 42677 42784 42822
## 1 1 1 1 1 1 1 1 1 1 1 1 2
## 42810 42898 42817 42929 42788 42916 42681 42732 42728 42931 42952 42868 42761
## 1 1 2 1 1 1 1 1 1 1 2 1 1
## 42946 42756 42940 42910 42937 42653 42772 42651 42884 42789 42684 42744 42808
## 1 1 1 2 1 1 1 1 1 1 1 1 2
## 42917 42811 42629 42741 42826 42655 42819 42874 42893 42661 42915 42821 42659
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 42899 42857 42691 42903 42880 42723 42851 42774 42632 42844
## 1 1 1 1 1 2 2 1 1 2
##
## Within cluster sum of squares by cluster:
## [1] 136.4363 127.4299
## (between_SS / total_SS = 61.8 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
library(cluster)##
## Attaching package: 'cluster'## The following object is masked from 'package:maps':
##
## votes.repubsil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.66 <- could potentially have a better algorithm## [1] 0.6552715fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 189 0.72
## 2 2 42 0.36
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 75% are in cluster 2 (higher ratings) <- minorities
# 25% are in cluster 1 (lower ratings) <- non-minorities
table(train$km.group, train$minority)##
## minority non-minority
## cl1 174 15
## cl2 4 38# cluster two has 75% of minority groups
# Are there significant differences?
aov_test = aov(RPL_EJI ~ km.group, data = train)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 2.491 2.4911 362.7 <2e-16 ***
## Residuals 229 1.573 0.0069
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(RPL_SVM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 3.918 3.918 276.7 <2e-16 ***
## Residuals 229 3.242 0.014
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(E_PM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 0.0197 0.019698 7.243 0.00764 **
## Residuals 229 0.6228 0.002719
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Testing Data
# Setting seed
set.seed(123)
z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 68.7%
kmeans_result ## K-means clustering with 2 clusters of sizes 19, 80
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -1.5919220 -1.7144558 -1.6815723
## 2 0.3780815 0.4071833 0.3993734
##
## Clustering vector:
## 42625 42626 42636 42639 42642 42643 42652 42662 42668 42669 42671 42673 42674
## 1 2 2 2 2 2 2 2 2 2 2 2 2
## 42680 42682 42687 42690 42693 42696 42698 42705 42707 42712 42717 42721 42722
## 2 2 2 2 2 2 2 2 2 2 1 1 2
## 42725 42727 42730 42739 42746 42747 42749 42750 42751 42753 42755 42757 42758
## 2 2 2 2 2 2 2 2 2 2 2 2 2
## 42759 42760 42765 42766 42767 42771 42773 42775 42776 42777 42783 42796 42798
## 2 2 2 2 2 2 1 2 2 2 2 2 2
## 42800 42802 42809 42813 42814 42815 42816 42820 42829 42830 42831 42833 42834
## 1 1 2 2 1 2 1 2 2 1 1 1 2
## 42836 42846 42847 42856 42860 42863 42866 42870 42877 42878 42881 42886 42894
## 1 1 1 2 2 2 2 1 2 2 2 2 2
## 42897 42901 42902 42904 42905 42909 42911 42913 42920 42921 42923 42924 42926
## 2 2 2 2 2 2 1 2 2 2 2 2 2
## 42927 42936 42938 42953 42955 42956 42957 42961
## 2 2 1 1 2 2 2 1
##
## Within cluster sum of squares by cluster:
## [1] 47.04045 51.77618
## (between_SS / total_SS = 66.4 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.68 <- could potentially have a better algorithm## [1] 0.6776646# all of cluster 1 remains under the average and has some negative values
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 19 0.40
## 2 2 80 0.74
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 88% are in cluster 1 (higher ratings) <- minorities
# 12% are in cluster 2 (lower ratings) <- non-minorities
table(test$km.group, test$minority)##
## minority non-minority
## cl1 3 16
## cl2 75 5# cluster 1 has 100% of minority groups
# Are there significant differences?
aov_test = aov(RPL_EJI ~ km.group, data = test)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 1.1116 1.1116 232.1 <2e-16 ***
## Residuals 97 0.4647 0.0048
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(RPL_SVM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 1.7002 1.7002 204.6 <2e-16 ***
## Residuals 97 0.8059 0.0083
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(E_PM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 0.02081 0.020810 7.805 0.00628 **
## Residuals 97 0.25862 0.002666
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1More Complex Model
Training Data
eji_base_bronx = eji_ny[which(eji_base$COUNTY == 'Bronx'),]
eji_base_bronx = na.omit(eji_base_bronx)
#Finding what variables to use from base model
#Above 0.60
correlation_matrix = cor(eji_base_bronx[, c(11:118)])## Warning in cor(eji_base_bronx[, c(11:118)]): the standard deviation is zerocorrelation_matrix## E_TOTPOP M_TOTPOP E_DAYPOP SPL_EJI RPL_EJI
## E_TOTPOP 1.000000000 0.913624562 0.536985177 0.236417590 0.220098142
## M_TOTPOP 0.913624562 1.000000000 0.489866799 0.275221724 0.266750288
## E_DAYPOP 0.536985177 0.489866799 1.000000000 0.117437390 0.105770495
## SPL_EJI 0.236417590 0.275221724 0.117437390 1.000000000 0.984167737
## RPL_EJI 0.220098142 0.266750288 0.105770495 0.984167737 1.000000000
## SPL_SER 0.236797420 0.266173527 0.159012269 0.867696259 0.872834600
## RPL_SER 0.209960783 0.244079073 0.135308331 0.849689863 0.877134806
## EPL_OZONE -0.086152598 -0.040797106 -0.064443835 -0.428683733 -0.395576041
## EPL_PM 0.077664639 0.078420374 -0.018283228 0.219251524 0.259574129
## EPL_DSLPM 0.113751822 0.056234593 0.044114534 0.529618513 0.518134116
## EPL_TOTCR 0.094435056 0.052723751 0.098293532 0.541795393 0.526645043
## SPL_EBM_THEME1 0.038009262 0.041901746 0.015444647 0.186606723 0.227586894
## RPL_EBM_DOM1 0.033511201 0.039679649 0.013425224 0.164712720 0.207292926
## EPL_NPL NA NA NA NA NA
## EPL_TRI -0.026527798 -0.063817597 0.048827533 0.279978463 0.263246293
## EPL_TSD -0.027435750 -0.030298401 0.165740246 -0.014974058 -0.005130206
## EPL_RMP 0.053541072 0.070376395 0.187665717 -0.047129642 -0.027357417
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.015747018 -0.006330987 0.227140161 0.227385803 0.229258930
## RPL_EBM_DOM2 0.031836776 0.003350790 0.192928315 0.245751889 0.248333400
## EPL_PARK 0.019553936 0.033953987 0.038519067 -0.221954214 -0.266994837
## EPL_HOUAGE 0.028027260 -0.003912778 -0.052436618 -0.170076081 -0.146944433
## EPL_WLKIND 0.268506365 0.271973165 0.059748723 0.155237321 0.132665235
## SPL_EBM_THEME3 0.167826777 0.146463230 -0.004873365 -0.058076270 -0.055605142
## RPL_EBM_DOM3 0.176313053 0.156045555 -0.004302228 -0.046663672 -0.043951243
## EPL_RAIL 0.070379914 0.066743492 0.044731298 0.419894579 0.493290595
## EPL_ROAD -0.023038579 -0.075837118 -0.146697063 0.082928635 0.113157484
## EPL_AIRPRT -0.009737170 0.027652409 0.331215926 0.076782106 0.062807797
## SPL_EBM_THEME4 0.046254624 0.044598774 0.154156026 0.414960061 0.478998831
## RPL_EBM_DOM4 0.051988494 0.045464679 0.099983777 0.419059170 0.488494966
## EPL_IMPWTR 0.038561491 0.052456103 -0.021906638 0.513525204 0.521641736
## SPL_EBM_THEME5 0.038561491 0.052456103 -0.021906638 0.513525204 0.521641736
## RPL_EBM_DOM5 0.038492890 0.052380312 -0.021988926 0.513531704 0.521661366
## SPL_EBM 0.108808769 0.084001096 0.215084797 0.341508796 0.368912381
## RPL_EBM 0.114522869 0.080443471 0.147715784 0.389062710 0.429100559
## EPL_MINRTY 0.214363665 0.262441712 0.017797712 0.707582693 0.711102717
## SPL_SVM_DOM1 0.214363665 0.262441712 0.017797712 0.707582693 0.711102717
## RPL_SVM_DOM1 0.214363665 0.262441712 0.017797712 0.707582693 0.711102717
## EPL_POV200 0.202090004 0.243440482 0.108402017 0.828979331 0.809151757
## EPL_NOHSDP 0.140459315 0.202449846 0.009897681 0.771515954 0.763078484
## EPL_UNEMP 0.138645725 0.176468974 0.097365607 0.464080469 0.440172547
## EPL_RENTER 0.224735903 0.247205073 0.155972046 0.679350497 0.672882894
## EPL_HOUBDN 0.072982701 0.153358948 0.012455246 0.695002091 0.714209929
## EPL_UNINSUR 0.175405402 0.220267541 0.052294103 0.419000606 0.433549379
## EPL_NOINT 0.134519359 0.164350897 0.064211504 0.649882575 0.613442157
## SPL_SVM_DOM2 0.207046198 0.264893943 0.097637151 0.833601585 0.820419046
## RPL_SVM_DOM2 0.197585538 0.262182685 0.090685237 0.825666288 0.823578049
## EPL_AGE65 -0.173335833 -0.200062762 -0.031674831 -0.477124765 -0.465894432
## EPL_AGE17 0.201259174 0.221374883 -0.018089749 0.576262009 0.548225297
## EPL_DISABL 0.005213395 -0.021609776 0.039906069 0.216310778 0.152617785
## EPL_LIMENG 0.173162374 0.158109944 0.045422018 0.500768878 0.491335408
## SPL_SVM_DOM3 0.087442846 0.062528891 0.001981533 0.382362295 0.329428704
## RPL_SVM_DOM3 0.121037732 0.095556369 0.014219920 0.381845605 0.334517415
## EPL_MOBILE -0.058135856 -0.043297846 -0.024719933 -0.002016489 -0.008480951
## EPL_GROUPQ 0.162360961 0.142615154 0.246840201 0.216106241 0.202954638
## SPL_SVM_DOM4 0.111784461 0.101966066 0.200900154 0.185427617 0.170940510
## RPL_SVM_DOM4 0.090832819 0.076581011 0.209366213 0.171879389 0.158663847
## SPL_SVM 0.231338235 0.270346532 0.132577113 0.852225176 0.824308531
## RPL_SVM 0.229862195 0.279759981 0.122998437 0.855826212 0.844185135
## F_BPHIGH 0.029018882 0.056477775 0.003944683 0.448499138 0.404320683
## F_ASTHMA 0.189883947 0.245741313 0.055312509 0.741420046 0.768079805
## F_CANCER -0.080458859 -0.148166148 0.024548769 -0.375328250 -0.360092986
## F_MHLTH 0.170660883 0.186228688 0.037223606 0.749225719 0.681200328
## F_DIABETES 0.194507961 0.256753711 0.050159952 0.808037101 0.822128705
## F_HVM 0.186490778 0.225262782 0.057041126 0.903994028 0.873446796
## RPL_HVM 0.186490778 0.225262782 0.057041126 0.903994028 0.873446796
## E_OZONE -0.064491773 -0.024845942 -0.041035312 -0.461650686 -0.432473057
## E_PM 0.076745301 0.077646920 -0.017960560 0.232085644 0.273295934
## E_DSLPM 0.126101355 0.065142298 0.024253193 0.500719267 0.475082311
## E_TOTCR 0.093322977 0.052597208 0.102668101 0.548922049 0.520393571
## E_NPL NA NA NA NA NA
## E_TRI -0.029465353 -0.058235484 0.049779838 0.299553805 0.280634702
## E_TSD -0.027435750 -0.030298401 0.165740246 -0.014974058 -0.005130206
## E_RMP 0.084025890 0.107208668 0.152795958 -0.024655354 -0.005354821
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK -0.018091031 -0.036007141 -0.036973389 0.218104212 0.262178305
## E_HOUAGE 0.027762532 -0.002710476 -0.052177602 -0.159236163 -0.136864795
## E_WLKIND -0.275150054 -0.275264854 -0.064151814 -0.161185819 -0.138309083
## E_RAIL 0.074087957 0.069866006 0.043575517 0.418816771 0.489642955
## E_ROAD -0.019435221 -0.069885206 -0.160865578 0.057853631 0.085331807
## E_AIRPRT 0.034347987 0.077884929 0.423779728 0.056042715 0.048252223
## E_IMPWTR 0.019083813 0.040494363 -0.036460865 0.483355038 0.499451485
## EP_MINRTY 0.223953727 0.272221808 0.021597292 0.715317565 0.721970354
## EP_POV200 0.180564658 0.207334560 0.115987510 0.805142223 0.767671292
## EP_NOHSDP 0.142116110 0.181519595 0.011166800 0.755227207 0.714616067
## EP_UNEMP 0.108648338 0.119303604 0.070496684 0.449828229 0.416421286
## EP_RENTER 0.233875973 0.243624730 0.151737335 0.728646914 0.708230402
## EP_HOUBDN 0.049183523 0.089727934 0.039455670 0.639389119 0.639001419
## EP_UNINSUR 0.178761415 0.226720802 0.066084694 0.387141230 0.397788252
## EP_NOINT 0.090422389 0.121999506 0.043346061 0.625370322 0.578503713
## EP_AGE65 -0.160133244 -0.195020522 0.006000718 -0.421463367 -0.412061868
## EP_AGE17 0.182831447 0.195758963 -0.071169371 0.523835363 0.495913306
## EP_DISABL -0.060611900 -0.070605168 0.088962968 0.181487960 0.126522377
## EP_LIMENG 0.173441610 0.159041731 0.001210396 0.512676896 0.500632794
## EP_MOBILE -0.081225911 -0.060258416 0.008028264 -0.044919676 -0.051002492
## EP_GROUPQ -0.107475004 -0.117557173 0.295105468 -0.040033128 -0.045044644
## EP_BPHIGH 0.090970931 0.120146853 -0.015970754 0.503024027 0.483819345
## EP_ASTHMA 0.138921307 0.185651234 0.013695233 0.763426251 0.726552279
## EP_CANCER -0.144992129 -0.179400052 -0.068758742 -0.511763363 -0.504149055
## EP_MHLTH 0.144089277 0.177001850 0.058676900 0.799612382 0.753046367
## EP_DIABETES 0.131260675 0.159736786 0.024572290 0.802809887 0.758125195
## EPL_BPHIGH 0.084142056 0.115766854 -0.020776721 0.553117083 0.532787761
## EPL_ASTHMA 0.200286128 0.259854111 0.058861106 0.831539421 0.826436568
## EPL_CANCER -0.143152608 -0.182268395 -0.041446714 -0.555457278 -0.547689410
## EPL_DIABETES 0.214146472 0.262310202 0.025061291 0.880001774 0.870364911
## EPL_MHLTH 0.168604433 0.213508039 0.067479328 0.849611389 0.807295449
## SPL_SER RPL_SER EPL_OZONE EPL_PM EPL_DSLPM
## E_TOTPOP 0.23679742 0.209960783 -0.0861525983 0.077664639 0.113751822
## M_TOTPOP 0.26617353 0.244079073 -0.0407971062 0.078420374 0.056234593
## E_DAYPOP 0.15901227 0.135308331 -0.0644438350 -0.018283228 0.044114534
## SPL_EJI 0.86769626 0.849689863 -0.4286837329 0.219251524 0.529618513
## RPL_EJI 0.87283460 0.877134806 -0.3955760408 0.259574129 0.518134116
## SPL_SER 1.00000000 0.985952176 -0.4040202170 0.209802604 0.573592414
## RPL_SER 0.98595218 1.000000000 -0.3639024355 0.232964427 0.567275354
## EPL_OZONE -0.40402022 -0.363902436 1.0000000000 -0.405490496 -0.656016657
## EPL_PM 0.20980260 0.232964427 -0.4054904955 1.000000000 0.117712366
## EPL_DSLPM 0.57359241 0.567275354 -0.6560166574 0.117712366 1.000000000
## EPL_TOTCR 0.60040855 0.590997282 -0.5922467180 -0.035416060 0.912638328
## SPL_EBM_THEME1 0.28495689 0.335868259 0.4175716748 -0.167635113 0.338597535
## RPL_EBM_DOM1 0.26353519 0.314723138 0.4473176797 -0.188555003 0.311645381
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.30872935 0.302932041 -0.1945416765 -0.434967818 0.424263179
## EPL_TSD 0.06446656 0.047945247 -0.1566698098 0.028302380 0.031767176
## EPL_RMP 0.14040268 0.126937172 0.0421618344 0.364259867 -0.245694425
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.42336364 0.404230974 -0.1728568011 -0.108099780 0.205595069
## RPL_EBM_DOM2 0.43730512 0.423911795 -0.1645777156 -0.109939934 0.228945656
## EPL_PARK -0.26498814 -0.316114708 0.1027411601 -0.242717122 -0.437531054
## EPL_HOUAGE -0.10846438 -0.101012806 0.2435356155 0.183241609 -0.164146419
## EPL_WLKIND 0.11890115 0.088419726 -0.0007498688 -0.028208586 -0.027718290
## SPL_EBM_THEME3 -0.03386746 -0.047901513 0.1899072157 0.108187358 -0.165992086
## RPL_EBM_DOM3 -0.02887955 -0.041665110 0.1797728852 0.098511393 -0.155844979
## EPL_RAIL 0.46252365 0.514414254 -0.2600131092 0.550929936 0.313668176
## EPL_ROAD 0.10583298 0.156854453 -0.0481040620 0.209951255 0.312381095
## EPL_AIRPRT 0.12007755 0.083527627 0.0189894942 -0.115957133 -0.001200832
## SPL_EBM_THEME4 0.47947424 0.521156140 -0.2227990218 0.469657077 0.362562241
## RPL_EBM_DOM4 0.48044257 0.527616878 -0.2335744115 0.508653310 0.353549505
## EPL_IMPWTR 0.58742262 0.591646197 -0.3116426487 0.067437483 0.670209666
## SPL_EBM_THEME5 0.58742262 0.591646197 -0.3116426487 0.067437483 0.670209666
## RPL_EBM_DOM5 0.58743188 0.591668966 -0.3117085133 0.067749081 0.670262476
## SPL_EBM 0.53324381 0.530840615 -0.1117936931 0.114761735 0.287073460
## RPL_EBM 0.57178450 0.589087671 -0.1360516566 0.175762632 0.365453091
## EPL_MINRTY 0.64777076 0.640529321 -0.2695310585 0.106143293 0.465308707
## SPL_SVM_DOM1 0.64777076 0.640529321 -0.2695310585 0.106143293 0.465308707
## RPL_SVM_DOM1 0.64777076 0.640529321 -0.2695310585 0.106143293 0.465308707
## EPL_POV200 0.86132762 0.833226524 -0.4657756149 0.145791038 0.585437843
## EPL_NOHSDP 0.79878661 0.785237825 -0.3307873110 0.079814128 0.540909562
## EPL_UNEMP 0.51524859 0.485275325 -0.2289710564 0.167913548 0.263959955
## EPL_RENTER 0.74619829 0.734290758 -0.4263690199 0.214532047 0.490569807
## EPL_HOUBDN 0.77524197 0.781127602 -0.2793740466 0.124128729 0.462721889
## EPL_UNINSUR 0.52020831 0.502657509 -0.2422174915 0.209788495 0.269620738
## EPL_NOINT 0.58965962 0.566484137 -0.3198283037 0.070246274 0.350367247
## SPL_SVM_DOM2 0.88839827 0.864177270 -0.4292829829 0.192081926 0.545331616
## RPL_SVM_DOM2 0.89065401 0.877672184 -0.3900392086 0.185973691 0.525740692
## EPL_AGE65 -0.52733260 -0.502111558 0.3910178194 -0.176559738 -0.461396971
## EPL_AGE17 0.60420158 0.562867599 -0.3803798535 0.089100861 0.433066178
## EPL_DISABL 0.18741996 0.153349626 -0.1207722880 -0.195053460 0.076654092
## EPL_LIMENG 0.64050369 0.614024166 -0.4355719120 0.072104341 0.578633620
## SPL_SVM_DOM3 0.39785785 0.356396027 -0.2202808707 -0.149312707 0.232062481
## RPL_SVM_DOM3 0.41213055 0.371642353 -0.2534842737 -0.114588010 0.255310690
## EPL_MOBILE 0.05780208 0.045622423 0.0498248129 0.073574363 -0.058452436
## EPL_GROUPQ 0.25864346 0.224903295 -0.1688388866 0.142184770 0.072120590
## SPL_SVM_DOM4 0.25120143 0.216176548 -0.1214127767 0.158415073 0.033791401
## RPL_SVM_DOM4 0.23590517 0.201705773 -0.1255589823 0.156038914 0.035190195
## SPL_SVM 0.91128509 0.871340366 -0.4440253424 0.160246404 0.528544921
## RPL_SVM 0.93167729 0.907370313 -0.4184665269 0.170758919 0.517805509
## F_BPHIGH 0.09062852 0.096252164 -0.0500606811 0.074811862 0.001284592
## F_ASTHMA 0.60828882 0.610828608 -0.2056385902 0.127574216 0.369474396
## F_CANCER -0.45890434 -0.451102288 0.1090961159 0.001306146 -0.322253436
## F_MHLTH 0.62618203 0.577127342 -0.5005157027 0.138448710 0.514378330
## F_DIABETES 0.60008497 0.594064883 -0.2780810656 0.157846128 0.394902804
## F_HVM 0.57186182 0.554228421 -0.3599591907 0.181379720 0.380683779
## RPL_HVM 0.57186182 0.554228421 -0.3599591907 0.181379720 0.380683779
## E_OZONE -0.46777224 -0.428659693 0.9499947598 -0.491456131 -0.633638854
## E_PM 0.22114459 0.245489244 -0.4115549334 0.999321251 0.130332644
## E_DSLPM 0.50821771 0.485092499 -0.7448073296 0.152086098 0.925446841
## E_TOTCR 0.58156249 0.557591646 -0.6864647278 -0.034041383 0.881819997
## E_NPL NA NA NA NA NA
## E_TRI 0.34071413 0.329454901 -0.2024853225 -0.427425385 0.427061268
## E_TSD 0.06446656 0.047945247 -0.1566698098 0.028302380 0.031767176
## E_RMP 0.13414527 0.124502377 0.0562840890 0.359569488 -0.233639863
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.26289863 0.314583104 -0.1016786951 0.237439544 0.446641296
## E_HOUAGE -0.09856411 -0.092205212 0.2413673119 0.182853726 -0.164459625
## E_WLKIND -0.12255745 -0.091167952 0.0063469283 0.026526036 0.025790004
## E_RAIL 0.45465588 0.502503469 -0.2703819252 0.565792846 0.307862072
## E_ROAD 0.07148056 0.119991233 -0.0431789518 0.204695478 0.265776912
## E_AIRPRT 0.08613470 0.058433021 -0.0101561321 -0.057491405 0.011710200
## E_IMPWTR 0.55638218 0.574087857 -0.2024118002 0.058183029 0.627646735
## EP_MINRTY 0.65563020 0.649215821 -0.2701006263 0.126112071 0.464074247
## EP_POV200 0.80204664 0.762280007 -0.4762353054 0.116415163 0.572094493
## EP_NOHSDP 0.74086755 0.700024492 -0.4473700903 0.102731879 0.557169195
## EP_UNEMP 0.46944657 0.438038552 -0.2157114810 0.127250113 0.265522974
## EP_RENTER 0.77218392 0.745425512 -0.5266106291 0.268508283 0.577875001
## EP_HOUBDN 0.70127045 0.687581320 -0.3333092722 0.197937527 0.471330780
## EP_UNINSUR 0.49043286 0.466539989 -0.2585903276 0.182253308 0.277092541
## EP_NOINT 0.54234049 0.512276256 -0.3179910478 0.048810163 0.338068309
## EP_AGE65 -0.49696890 -0.478725003 0.2949709156 -0.111483773 -0.414123355
## EP_AGE17 0.53041881 0.492998865 -0.3388139400 0.069167252 0.391802997
## EP_DISABL 0.15020626 0.122140094 -0.0588487253 -0.183304900 0.044501365
## EP_LIMENG 0.62333777 0.584887716 -0.5030351477 0.258820646 0.591527463
## EP_MOBILE 0.01582468 0.007645493 0.0661825118 0.069930326 -0.104555143
## EP_GROUPQ -0.05109770 -0.056070078 -0.0009120689 0.013192679 -0.057684273
## EP_BPHIGH 0.16384573 0.168318182 -0.0741811218 0.058537233 0.056369495
## EP_ASTHMA 0.53972592 0.525440594 -0.2713203715 0.158729763 0.329583370
## EP_CANCER -0.62688169 -0.606695626 0.2992522651 -0.128339430 -0.481525866
## EP_MHLTH 0.73609471 0.697477700 -0.4388848281 0.109123886 0.539932183
## EP_DIABETES 0.60986096 0.581791705 -0.3546924579 0.036819009 0.442053955
## EPL_BPHIGH 0.19872627 0.201418578 -0.0978684059 0.061954722 0.080803486
## EPL_ASTHMA 0.66040154 0.656776170 -0.2741081652 0.161978489 0.408227530
## EPL_CANCER -0.64963846 -0.628415850 0.3460226356 -0.158106525 -0.495368750
## EPL_DIABETES 0.70902113 0.690546881 -0.3594241782 0.108871825 0.482848881
## EPL_MHLTH 0.79107013 0.751169965 -0.4738583939 0.150326074 0.567114614
## EPL_TOTCR SPL_EBM_THEME1 RPL_EBM_DOM1 EPL_NPL EPL_TRI
## E_TOTPOP 0.09443506 0.038009262 0.033511201 NA -0.026527798
## M_TOTPOP 0.05272375 0.041901746 0.039679649 NA -0.063817597
## E_DAYPOP 0.09829353 0.015444647 0.013425224 NA 0.048827533
## SPL_EJI 0.54179539 0.186606723 0.164712720 NA 0.279978463
## RPL_EJI 0.52664504 0.227586894 0.207292926 NA 0.263246293
## SPL_SER 0.60040855 0.284956886 0.263535185 NA 0.308729347
## RPL_SER 0.59099728 0.335868259 0.314723138 NA 0.302932041
## EPL_OZONE -0.59224672 0.417571675 0.447317680 NA -0.194541676
## EPL_PM -0.03541606 -0.167635113 -0.188555003 NA -0.434967818
## EPL_DSLPM 0.91263833 0.338597535 0.311645381 NA 0.424263179
## EPL_TOTCR 1.00000000 0.426643326 0.397113016 NA 0.509230030
## SPL_EBM_THEME1 0.42664333 1.000000000 0.995492236 NA 0.192986337
## RPL_EBM_DOM1 0.39711302 0.995492236 1.000000000 NA 0.191836916
## EPL_NPL NA NA NA 1 NA
## EPL_TRI 0.50923003 0.192986337 0.191836916 NA 1.000000000
## EPL_TSD 0.07838808 -0.112310096 -0.113439155 NA 0.042951266
## EPL_RMP -0.20125707 -0.072627426 -0.086608483 NA -0.425070630
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.33091523 0.109118175 0.096115786 NA 0.609635189
## RPL_EBM_DOM2 0.34498985 0.139590807 0.126683721 NA 0.637062127
## EPL_PARK -0.45105127 -0.513796660 -0.478057324 NA -0.117386231
## EPL_HOUAGE -0.25870074 0.094180174 0.103853363 NA -0.251818698
## EPL_WLKIND -0.02218901 -0.040747393 -0.031910857 NA -0.062401127
## SPL_EBM_THEME3 -0.23526175 0.017402271 0.031699815 NA -0.231275978
## RPL_EBM_DOM3 -0.22394932 0.014177918 0.027966417 NA -0.221720051
## EPL_RAIL 0.27856072 0.217801283 0.194245830 NA 0.143588319
## EPL_ROAD 0.25918223 0.352948547 0.325819053 NA 0.001299763
## EPL_AIRPRT 0.07537599 0.054900916 0.060941169 NA 0.073180087
## SPL_EBM_THEME4 0.35405933 0.323864665 0.298399670 NA 0.156414658
## RPL_EBM_DOM4 0.33644497 0.304457000 0.278615945 NA 0.150557671
## EPL_IMPWTR 0.65631427 0.435784578 0.414863221 NA 0.261574097
## SPL_EBM_THEME5 0.65631427 0.435784578 0.414863221 NA 0.261574097
## RPL_EBM_DOM5 0.65629251 0.435806651 0.414885111 NA 0.261440115
## SPL_EBM 0.35153955 0.315671680 0.301810480 NA 0.438397104
## RPL_EBM 0.41199732 0.386721353 0.368554789 NA 0.462606186
## EPL_MINRTY 0.46309872 0.261310406 0.246182348 NA 0.194064392
## SPL_SVM_DOM1 0.46309872 0.261310406 0.246182348 NA 0.194064392
## RPL_SVM_DOM1 0.46309872 0.261310406 0.246182348 NA 0.194064392
## EPL_POV200 0.60825273 0.190194985 0.169849201 NA 0.186357391
## EPL_NOHSDP 0.55096306 0.276663542 0.261787681 NA 0.191592255
## EPL_UNEMP 0.24076370 0.066084342 0.056415727 NA 0.001741317
## EPL_RENTER 0.48801137 0.124829201 0.103604662 NA 0.095680044
## EPL_HOUBDN 0.46845147 0.259412598 0.247894011 NA 0.118651030
## EPL_UNINSUR 0.26206046 0.086324772 0.072703112 NA 0.036651086
## EPL_NOINT 0.36255163 0.051610189 0.044517064 NA 0.178431465
## SPL_SVM_DOM2 0.54845281 0.186563498 0.168212079 NA 0.147563820
## RPL_SVM_DOM2 0.53318474 0.216049803 0.197808015 NA 0.139346834
## EPL_AGE65 -0.44211740 -0.104919158 -0.087561646 NA -0.078087999
## EPL_AGE17 0.44524306 0.081650012 0.065691551 NA 0.135760436
## EPL_DISABL 0.12788727 -0.087137546 -0.087501348 NA 0.136819732
## EPL_LIMENG 0.54659986 0.141141176 0.138467818 NA 0.175387407
## SPL_SVM_DOM3 0.27388249 -0.017038984 -0.017553714 NA 0.184164212
## RPL_SVM_DOM3 0.29452282 -0.021647142 -0.023385609 NA 0.175284013
## EPL_MOBILE -0.05537384 0.023359316 0.015466929 NA -0.100201911
## EPL_GROUPQ 0.05093613 -0.101501276 -0.106331021 NA 0.034664308
## SPL_SVM_DOM4 0.01701494 -0.076195834 -0.084198928 NA -0.018814990
## RPL_SVM_DOM4 0.01925667 -0.080011273 -0.087103872 NA -0.014619463
## SPL_SVM 0.53722430 0.139600686 0.121895853 NA 0.173587503
## RPL_SVM 0.52896873 0.166391471 0.149053923 NA 0.160955864
## F_BPHIGH 0.02968036 -0.009427114 -0.019198914 NA 0.086844456
## F_ASTHMA 0.38710368 0.253501244 0.242059317 NA 0.083352157
## F_CANCER -0.33769348 -0.272505896 -0.262212459 NA -0.032384606
## F_MHLTH 0.48442590 0.001398471 -0.018807220 NA 0.204914006
## F_DIABETES 0.38388035 0.172655015 0.160046204 NA 0.169680606
## F_HVM 0.37771492 0.062867095 0.045160206 NA 0.196511039
## RPL_HVM 0.37771492 0.062867095 0.045160206 NA 0.196511039
## E_OZONE -0.56929819 0.347831493 0.377536175 NA -0.100098825
## E_PM -0.02242667 -0.159801207 -0.181080242 NA -0.414482911
## E_DSLPM 0.80365188 0.107050248 0.088296157 NA 0.394468255
## E_TOTCR 0.96790166 0.262457904 0.236445119 NA 0.528749343
## E_NPL NA NA NA NA NA
## E_TRI 0.52416982 0.200533258 0.196014054 NA 0.963097211
## E_TSD 0.07838808 -0.112310096 -0.113439155 NA 0.042951266
## E_RMP -0.19548357 -0.046674352 -0.057373130 NA -0.431159469
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.45809461 0.522622861 0.486470510 NA 0.115558251
## E_HOUAGE -0.25822624 0.091533612 0.101469322 NA -0.251081371
## E_WLKIND 0.01829926 0.043231621 0.034377165 NA 0.056343199
## E_RAIL 0.25359260 0.183724485 0.160536284 NA 0.123387513
## E_ROAD 0.20668811 0.293575534 0.269314204 NA -0.011489750
## E_AIRPRT 0.05363417 0.020483127 0.024817888 NA 0.048014694
## E_IMPWTR 0.62470233 0.534639078 0.511168620 NA 0.235565673
## EP_MINRTY 0.46318639 0.267715739 0.251503422 NA 0.184168508
## EP_POV200 0.59751211 0.151260337 0.130632898 NA 0.212476186
## EP_NOHSDP 0.55717208 0.141142220 0.126585365 NA 0.215051049
## EP_UNEMP 0.27054576 0.097893937 0.088992811 NA 0.020096240
## EP_RENTER 0.56071572 0.106881266 0.085732156 NA 0.102321951
## EP_HOUBDN 0.46662100 0.215942477 0.201161486 NA 0.069158787
## EP_UNINSUR 0.26898163 0.063182946 0.050521786 NA 0.058407643
## EP_NOINT 0.35436592 0.034703911 0.029634659 NA 0.203403721
## EP_AGE65 -0.39903419 -0.153100684 -0.137967570 NA -0.076331840
## EP_AGE17 0.38860847 0.062886272 0.052564591 NA 0.128508737
## EP_DISABL 0.12030412 -0.016989939 -0.027866235 NA 0.126213932
## EP_LIMENG 0.49695376 0.076484393 0.063262797 NA 0.054913722
## EP_MOBILE -0.10546776 -0.017784746 -0.028370284 NA -0.091822548
## EP_GROUPQ -0.01327566 -0.025295719 -0.031492481 NA -0.026776012
## EP_BPHIGH 0.07175820 0.008750381 0.001018599 NA 0.156466898
## EP_ASTHMA 0.33347592 0.114799784 0.096877803 NA 0.151576180
## EP_CANCER -0.48134026 -0.252373655 -0.233497560 NA -0.108669031
## EP_MHLTH 0.54507544 0.138218859 0.120503494 NA 0.218033515
## EP_DIABETES 0.47042865 0.123235831 0.105066503 NA 0.279482035
## EPL_BPHIGH 0.09739123 0.010304047 0.003616770 NA 0.185611430
## EPL_ASTHMA 0.41953630 0.217779047 0.197245339 NA 0.149973821
## EPL_CANCER -0.49076434 -0.214421889 -0.198109371 NA -0.102946278
## EPL_DIABETES 0.49251270 0.176555493 0.159763160 NA 0.263771910
## EPL_MHLTH 0.56784545 0.136835308 0.117036765 NA 0.201800660
## EPL_TSD EPL_RMP EPL_COAL EPL_LEAD SPL_EBM_THEME2
## E_TOTPOP -0.0274357505 0.053541072 NA NA 0.015747018
## M_TOTPOP -0.0302984012 0.070376395 NA NA -0.006330987
## E_DAYPOP 0.1657402457 0.187665717 NA NA 0.227140161
## SPL_EJI -0.0149740580 -0.047129642 NA NA 0.227385803
## RPL_EJI -0.0051302064 -0.027357417 NA NA 0.229258930
## SPL_SER 0.0644665565 0.140402678 NA NA 0.423363639
## RPL_SER 0.0479452470 0.126937172 NA NA 0.404230974
## EPL_OZONE -0.1566698098 0.042161834 NA NA -0.172856801
## EPL_PM 0.0283023798 0.364259867 NA NA -0.108099780
## EPL_DSLPM 0.0317671760 -0.245694425 NA NA 0.205595069
## EPL_TOTCR 0.0783880810 -0.201257071 NA NA 0.330915230
## SPL_EBM_THEME1 -0.1123100959 -0.072627426 NA NA 0.109118175
## RPL_EBM_DOM1 -0.1134391549 -0.086608483 NA NA 0.096115786
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.0429512662 -0.425070630 NA NA 0.609635189
## EPL_TSD 1.0000000000 0.120206297 NA NA 0.278509748
## EPL_RMP 0.1202062973 1.000000000 NA NA 0.447956692
## EPL_COAL NA NA 1 NA NA
## EPL_LEAD NA NA NA 1 NA
## SPL_EBM_THEME2 0.2785097475 0.447956692 NA NA 1.000000000
## RPL_EBM_DOM2 0.1394121791 0.414746193 NA NA 0.979501699
## EPL_PARK -0.0042357890 -0.032197462 NA NA -0.140412866
## EPL_HOUAGE -0.1222079044 0.150314601 NA NA -0.132346396
## EPL_WLKIND 0.0787410995 0.020177361 NA NA -0.032278845
## SPL_EBM_THEME3 -0.0499299621 0.122500719 NA NA -0.126122727
## RPL_EBM_DOM3 -0.0606446221 0.116715054 NA NA -0.123261008
## EPL_RAIL 0.0121470949 0.084695329 NA NA 0.210765347
## EPL_ROAD -0.0051296945 -0.069363482 NA NA -0.057715646
## EPL_AIRPRT -0.0052781575 0.212842522 NA NA 0.248383602
## SPL_EBM_THEME4 0.0058172590 0.153786302 NA NA 0.280263497
## RPL_EBM_DOM4 0.0060755477 0.131134117 NA NA 0.255643154
## EPL_IMPWTR 0.0300239152 -0.059233560 NA NA 0.205666505
## SPL_EBM_THEME5 0.0300239152 -0.059233560 NA NA 0.205666505
## RPL_EBM_DOM5 0.0299704952 -0.059203726 NA NA 0.205555551
## SPL_EBM 0.1793230472 0.424801387 NA NA 0.802500753
## RPL_EBM 0.0955839242 0.343380872 NA NA 0.745957573
## EPL_MINRTY -0.0035761585 -0.101723260 NA NA 0.100530258
## SPL_SVM_DOM1 -0.0035761585 -0.101723260 NA NA 0.100530258
## RPL_SVM_DOM1 -0.0035761585 -0.101723260 NA NA 0.100530258
## EPL_POV200 0.0231118450 0.039910276 NA NA 0.215734271
## EPL_NOHSDP -0.0137064998 -0.031488784 NA NA 0.155771639
## EPL_UNEMP 0.0308180322 0.048348153 NA NA 0.046485180
## EPL_RENTER 0.0292949026 0.106275767 NA NA 0.185197327
## EPL_HOUBDN 0.0143047804 0.050127733 NA NA 0.158061682
## EPL_UNINSUR 0.0776121643 0.071180277 NA NA 0.105583507
## EPL_NOINT -0.0375231166 -0.127109679 NA NA 0.059558973
## SPL_SVM_DOM2 0.0258450985 0.029767492 NA NA 0.170312234
## RPL_SVM_DOM2 0.0285580977 0.042114349 NA NA 0.173158085
## EPL_AGE65 -0.0685996975 -0.046898770 NA NA -0.123773238
## EPL_AGE17 0.0481932640 -0.040367791 NA NA 0.103102526
## EPL_DISABL 0.0180854079 -0.189821990 NA NA -0.025524276
## EPL_LIMENG -0.0327240263 0.041655651 NA NA 0.199051389
## SPL_SVM_DOM3 -0.0142739571 -0.159840115 NA NA 0.040741676
## RPL_SVM_DOM3 -0.0004315695 -0.142814509 NA NA 0.048397012
## EPL_MOBILE -0.0216838799 0.095797679 NA NA -0.018762775
## EPL_GROUPQ 0.0672258159 0.038610325 NA NA 0.074900368
## SPL_SVM_DOM4 0.0474452102 0.079878680 NA NA 0.055485257
## RPL_SVM_DOM4 0.0579687572 0.077877025 NA NA 0.059269112
## SPL_SVM 0.0288240197 -0.006581657 NA NA 0.165189450
## RPL_SVM 0.0340586354 0.014305053 NA NA 0.171310626
## F_BPHIGH -0.0464497820 -0.218926516 NA NA -0.106784538
## F_ASTHMA 0.0232974312 -0.055936757 NA NA 0.036275963
## F_CANCER -0.0180662871 -0.023075228 NA NA -0.052961601
## F_MHLTH -0.0603938442 -0.091089185 NA NA 0.112145323
## F_DIABETES -0.1134977905 -0.137623004 NA NA 0.031966733
## F_HVM -0.0801584128 -0.198536139 NA NA 0.011122415
## RPL_HVM -0.0801584128 -0.198536139 NA NA 0.011122415
## E_OZONE -0.1045026123 -0.065063562 NA NA -0.165073029
## E_PM 0.0296409991 0.349192690 NA NA -0.100891064
## E_DSLPM 0.0234050628 -0.284350478 NA NA 0.143356168
## E_TOTCR 0.1190529215 -0.230738860 NA NA 0.330446706
## E_NPL NA NA NA NA NA
## E_TRI 0.0475294973 -0.386900033 NA NA 0.606864672
## E_TSD 1.0000000000 0.120206297 NA NA 0.278509748
## E_RMP 0.0341492711 0.896123297 NA NA 0.343122863
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.0041698278 0.031696072 NA NA 0.138226307
## E_HOUAGE -0.1235347631 0.148042179 NA NA -0.133727587
## E_WLKIND -0.0815413585 -0.016706045 NA NA 0.028992462
## E_RAIL 0.0127833370 0.089576305 NA NA 0.195542280
## E_ROAD 0.0056336013 -0.089957477 NA NA -0.085836689
## E_AIRPRT -0.0035611889 0.161622584 NA NA 0.181412698
## E_IMPWTR 0.0223267351 -0.046561360 NA NA 0.190272309
## EP_MINRTY 0.0017535280 -0.078913526 NA NA 0.110908365
## EP_POV200 0.0096792609 0.000980073 NA NA 0.206298440
## EP_NOHSDP -0.0379191476 -0.069960507 NA NA 0.142696126
## EP_UNEMP 0.0082596533 0.025005213 NA NA 0.041439288
## EP_RENTER 0.0285424398 0.116686274 NA NA 0.200221472
## EP_HOUBDN -0.0078545072 0.074778915 NA NA 0.128194901
## EP_UNINSUR 0.0930861881 0.041250770 NA NA 0.103455870
## EP_NOINT -0.0400449515 -0.148683350 NA NA 0.065087803
## EP_AGE65 -0.0877480636 -0.053899001 NA NA -0.130575343
## EP_AGE17 0.0375029460 -0.073120735 NA NA 0.067165490
## EP_DISABL 0.0025869926 -0.135419607 NA NA 0.007871444
## EP_LIMENG -0.0543647464 0.158825284 NA NA 0.178769006
## EP_MOBILE -0.0177569198 0.067653614 NA NA -0.033817499
## EP_GROUPQ 0.0812986482 0.062434340 NA NA 0.037795771
## EP_BPHIGH -0.0727846350 -0.326134775 NA NA -0.133532099
## EP_ASTHMA -0.0400409764 -0.195431172 NA NA -0.023978069
## EP_CANCER -0.0624671550 -0.108306518 NA NA -0.203903812
## EP_MHLTH -0.0006942556 -0.069070451 NA NA 0.151381971
## EP_DIABETES -0.0446842377 -0.208489024 NA NA 0.087318000
## EPL_BPHIGH -0.0860034297 -0.348862864 NA NA -0.126421723
## EPL_ASTHMA -0.0180318128 -0.116022446 NA NA 0.044184971
## EPL_CANCER -0.0503484066 -0.089834324 NA NA -0.181237072
## EPL_DIABETES -0.0344711114 -0.180298396 NA NA 0.097294950
## EPL_MHLTH 0.0085251856 -0.045985577 NA NA 0.156432407
## RPL_EBM_DOM2 EPL_PARK EPL_HOUAGE EPL_WLKIND
## E_TOTPOP 0.031836776 0.019553936 0.028027260 0.2685063650
## M_TOTPOP 0.003350790 0.033953987 -0.003912778 0.2719731649
## E_DAYPOP 0.192928315 0.038519067 -0.052436618 0.0597487229
## SPL_EJI 0.245751889 -0.221954214 -0.170076081 0.1552373213
## RPL_EJI 0.248333400 -0.266994837 -0.146944433 0.1326652347
## SPL_SER 0.437305123 -0.264988136 -0.108464376 0.1189011480
## RPL_SER 0.423911795 -0.316114708 -0.101012806 0.0884197260
## EPL_OZONE -0.164577716 0.102741160 0.243535615 -0.0007498688
## EPL_PM -0.109939934 -0.242717122 0.183241609 -0.0282085864
## EPL_DSLPM 0.228945656 -0.437531054 -0.164146419 -0.0277182897
## EPL_TOTCR 0.344989847 -0.451051270 -0.258700740 -0.0221890094
## SPL_EBM_THEME1 0.139590807 -0.513796660 0.094180174 -0.0407473932
## RPL_EBM_DOM1 0.126683721 -0.478057324 0.103853363 -0.0319108572
## EPL_NPL NA NA NA NA
## EPL_TRI 0.637062127 -0.117386231 -0.251818698 -0.0624011265
## EPL_TSD 0.139412179 -0.004235789 -0.122207904 0.0787410995
## EPL_RMP 0.414746193 -0.032197462 0.150314601 0.0201773611
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.979501699 -0.140412866 -0.132346396 -0.0322788454
## RPL_EBM_DOM2 1.000000000 -0.152809576 -0.122281181 -0.0532398459
## EPL_PARK -0.152809576 1.000000000 -0.009673341 0.0904999772
## EPL_HOUAGE -0.122281181 -0.009673341 1.000000000 0.1550684735
## EPL_WLKIND -0.053239846 0.090499977 0.155068474 1.0000000000
## SPL_EBM_THEME3 -0.130637574 0.103362145 0.838856411 0.6644191459
## RPL_EBM_DOM3 -0.124438620 0.112135293 0.791126899 0.6942228593
## EPL_RAIL 0.220041267 -0.410074280 0.032927192 -0.0550527728
## EPL_ROAD -0.020360401 -0.614757384 0.147035024 -0.0719297862
## EPL_AIRPRT 0.184586540 -0.007355506 -0.010749280 0.0881845204
## SPL_EBM_THEME4 0.268440747 -0.545768645 0.070050210 -0.0254513877
## RPL_EBM_DOM4 0.252253575 -0.525614017 0.071303191 -0.0301711449
## EPL_IMPWTR 0.208617102 -0.380246308 -0.105457318 0.0083896174
## SPL_EBM_THEME5 0.208617102 -0.380246308 -0.105457318 0.0083896174
## RPL_EBM_DOM5 0.208500161 -0.380289441 -0.105282314 0.0083574287
## SPL_EBM 0.784181164 -0.312747835 0.298991840 0.2637381118
## RPL_EBM 0.760511832 -0.413419241 0.284761977 0.2121887246
## EPL_MINRTY 0.119063218 -0.164898023 -0.208600232 0.1182704468
## SPL_SVM_DOM1 0.119063218 -0.164898023 -0.208600232 0.1182704468
## RPL_SVM_DOM1 0.119063218 -0.164898023 -0.208600232 0.1182704468
## EPL_POV200 0.232851987 -0.146630472 -0.257196871 0.0616291468
## EPL_NOHSDP 0.178389995 -0.189302928 -0.228682769 0.0415484928
## EPL_UNEMP 0.044955393 -0.061832330 -0.071443587 0.1131606007
## EPL_RENTER 0.201159143 -0.147623706 -0.143439973 0.0497844182
## EPL_HOUBDN 0.170064865 -0.082098188 -0.163768879 0.0286358729
## EPL_UNINSUR 0.101022834 -0.049479157 -0.077628055 -0.0141648404
## EPL_NOINT 0.065754903 -0.079235641 -0.277261166 0.1010488989
## SPL_SVM_DOM2 0.181892090 -0.136837227 -0.226740299 0.0737287881
## RPL_SVM_DOM2 0.185714453 -0.142458330 -0.216414925 0.0683545548
## EPL_AGE65 -0.130091964 0.089834113 0.231338787 0.0131230939
## EPL_AGE17 0.110710674 -0.106389154 -0.294067411 0.0087928701
## EPL_DISABL -0.030448172 0.044155930 -0.076803611 0.0725867982
## EPL_LIMENG 0.235824333 -0.120525569 -0.167328107 -0.0104385702
## SPL_SVM_DOM3 0.051560915 -0.030296022 -0.154449619 0.0545141428
## RPL_SVM_DOM3 0.058310650 -0.045440110 -0.162333670 0.0422875342
## EPL_MOBILE -0.022956425 -0.030218104 0.109361782 0.0233952064
## EPL_GROUPQ 0.056349801 0.033298321 -0.219624928 -0.1164666477
## SPL_SVM_DOM4 0.037445146 0.014031060 -0.136274245 -0.0890871500
## RPL_SVM_DOM4 0.038982933 0.013152489 -0.134816490 -0.0903088097
## SPL_SVM 0.173520866 -0.123118527 -0.270571098 0.0564091016
## RPL_SVM 0.181384658 -0.130908838 -0.254613219 0.0469223215
## F_BPHIGH -0.101641740 -0.064731235 -0.042366227 0.1430608252
## F_ASTHMA 0.043574415 -0.181813563 -0.140598385 0.1245054588
## F_CANCER -0.061487498 0.128144304 0.177516415 -0.0276231710
## F_MHLTH 0.130527375 -0.084163326 -0.299305057 0.0724528904
## F_DIABETES 0.056974493 -0.158167635 -0.135516895 0.0980545445
## F_HVM 0.029440863 -0.138375542 -0.187385794 0.1539210143
## RPL_HVM 0.029440863 -0.138375542 -0.187385794 0.1539210143
## E_OZONE -0.160424340 0.150559773 0.214520437 0.0024282690
## E_PM -0.102784945 -0.252658442 0.178638640 -0.0330481179
## E_DSLPM 0.163830053 -0.172596367 -0.164506906 0.0024881457
## E_TOTCR 0.337265448 -0.290855426 -0.282768918 0.0088411151
## E_NPL NA NA NA NA
## E_TRI 0.629408560 -0.103912935 -0.266071222 -0.0748555800
## E_TSD 0.139412179 -0.004235789 -0.122207904 0.0787410995
## E_RMP 0.345204762 -0.027119845 0.168090693 0.0285204344
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.150429971 -0.997432555 0.012842041 -0.0893822296
## E_HOUAGE -0.124291225 -0.007147892 0.997562969 0.1582561348
## E_WLKIND 0.049502194 -0.090129534 -0.156606681 -0.9953438933
## E_RAIL 0.202355984 -0.376793799 0.051542890 -0.0685464881
## E_ROAD -0.045055195 -0.528494556 0.146240353 -0.0702138992
## E_AIRPRT 0.133659634 -0.004962782 -0.008759735 0.0189889910
## E_IMPWTR 0.190060640 -0.497401248 -0.078525931 0.0011482188
## EP_MINRTY 0.127452928 -0.178276677 -0.201077156 0.1195953051
## EP_POV200 0.223847971 -0.126106496 -0.270817768 0.0957925294
## EP_NOHSDP 0.169042912 -0.134062809 -0.219888092 0.0953650967
## EP_UNEMP 0.032612698 -0.067780865 -0.073034636 0.1283088875
## EP_RENTER 0.220206609 -0.142212961 -0.167462954 0.0682266030
## EP_HOUBDN 0.134755502 -0.098877679 -0.142754999 0.0458791385
## EP_UNINSUR 0.099685162 -0.050027769 -0.063239004 0.0040662948
## EP_NOINT 0.073324698 -0.073512125 -0.265890125 0.1358317725
## EP_AGE65 -0.132023427 0.063811507 0.221436113 0.0491738921
## EP_AGE17 0.074920807 -0.093161785 -0.284420681 0.0344459547
## EP_DISABL 0.006157561 0.032055882 -0.010672721 0.0977588422
## EP_LIMENG 0.215796902 -0.102288713 -0.034525574 0.0120623395
## EP_MOBILE -0.037171877 -0.024745592 0.110700188 -0.0014088667
## EP_GROUPQ 0.017959260 0.072471729 -0.047514833 -0.0179291513
## EP_BPHIGH -0.122366888 -0.088192505 -0.038972928 0.1988599480
## EP_ASTHMA -0.015813661 -0.120552460 -0.236022453 0.1782583108
## EP_CANCER -0.206628667 0.108154514 0.220545429 0.0361372792
## EP_MHLTH 0.165150532 -0.111401035 -0.279362115 0.1028982691
## EP_DIABETES 0.113043802 -0.138833019 -0.219821892 0.2063477538
## EPL_BPHIGH -0.112854794 -0.095711980 -0.064354407 0.1861042626
## EPL_ASTHMA 0.054500693 -0.158135593 -0.211673173 0.1176467572
## EPL_CANCER -0.185696943 0.127818388 0.235221283 0.0107675480
## EPL_DIABETES 0.125853235 -0.199783205 -0.187348561 0.1600281024
## EPL_MHLTH 0.168493146 -0.124698627 -0.284204020 0.0655590577
## SPL_EBM_THEME3 RPL_EBM_DOM3 EPL_RAIL EPL_ROAD
## E_TOTPOP 0.167826777 0.176313053 0.0703799141 -0.0230385786
## M_TOTPOP 0.146463230 0.156045555 0.0667434915 -0.0758371178
## E_DAYPOP -0.004873365 -0.004302228 0.0447312975 -0.1466970627
## SPL_EJI -0.058076270 -0.046663672 0.4198945789 0.0829286351
## RPL_EJI -0.055605142 -0.043951243 0.4932905949 0.1131574844
## SPL_SER -0.033867464 -0.028879554 0.4625236504 0.1058329848
## RPL_SER -0.047901513 -0.041665110 0.5144142542 0.1568544533
## EPL_OZONE 0.189907216 0.179772885 -0.2600131092 -0.0481040620
## EPL_PM 0.108187358 0.098511393 0.5509299356 0.2099512552
## EPL_DSLPM -0.165992086 -0.155844979 0.3136681760 0.3123810946
## EPL_TOTCR -0.235261754 -0.223949321 0.2785607191 0.2591822297
## SPL_EBM_THEME1 0.017402271 0.014177918 0.2178012834 0.3529485475
## RPL_EBM_DOM1 0.031699815 0.027966417 0.1942458299 0.3258190528
## EPL_NPL NA NA NA NA
## EPL_TRI -0.231275978 -0.221720051 0.1435883188 0.0012997632
## EPL_TSD -0.049929962 -0.060644622 0.0121470949 -0.0051296945
## EPL_RMP 0.122500719 0.116715054 0.0846953286 -0.0693634821
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 -0.126122727 -0.123261008 0.2107653475 -0.0577156461
## RPL_EBM_DOM2 -0.130637574 -0.124438620 0.2200412666 -0.0203604014
## EPL_PARK 0.103362145 0.112135293 -0.4100742796 -0.6147573842
## EPL_HOUAGE 0.838856411 0.791126899 0.0329271923 0.1470350239
## EPL_WLKIND 0.664419146 0.694222859 -0.0550527728 -0.0719297862
## SPL_EBM_THEME3 1.000000000 0.980627890 -0.0302264761 0.0342164545
## RPL_EBM_DOM3 0.980627890 1.000000000 -0.0274796632 0.0043087562
## EPL_RAIL -0.030226476 -0.027479663 1.0000000000 0.2402699942
## EPL_ROAD 0.034216454 0.004308756 0.2402699942 1.0000000000
## EPL_AIRPRT 0.039194930 0.038467347 -0.0131136129 -0.5152649739
## SPL_EBM_THEME4 0.005487987 -0.002344521 0.9047147339 0.2700629657
## RPL_EBM_DOM4 0.005120361 -0.003026523 0.9508212368 0.2961119086
## EPL_IMPWTR -0.098564395 -0.084239776 0.2337696022 0.2628146628
## SPL_EBM_THEME5 -0.098564395 -0.084239776 0.2337696022 0.2628146628
## RPL_EBM_DOM5 -0.098452283 -0.084141029 0.2338474761 0.2629172136
## SPL_EBM 0.349459606 0.341447029 0.4768229895 0.1141012261
## RPL_EBM 0.304579602 0.293658956 0.5769911032 0.2681720615
## EPL_MINRTY -0.103686841 -0.085137599 0.2251723555 0.0338805017
## SPL_SVM_DOM1 -0.103686841 -0.085137599 0.2251723555 0.0338805017
## RPL_SVM_DOM1 -0.103686841 -0.085137599 0.2251723555 0.0338805017
## EPL_POV200 -0.169955398 -0.154852510 0.2644038087 0.0374092583
## EPL_NOHSDP -0.161922496 -0.160967796 0.2123582908 0.0989376160
## EPL_UNEMP 0.003514276 0.017694135 0.1461135935 -0.0180541962
## EPL_RENTER -0.090494822 -0.083373815 0.3259213715 0.0819498243
## EPL_HOUBDN -0.113268950 -0.100655151 0.2934148780 0.0209793983
## EPL_UNINSUR -0.069367586 -0.069167342 0.2491910032 0.0007849773
## EPL_NOINT -0.159604957 -0.154224629 0.2005765504 -0.0153499485
## SPL_SVM_DOM2 -0.139788869 -0.128907408 0.3112558207 0.0325610750
## RPL_SVM_DOM2 -0.135246240 -0.124241274 0.3193250064 0.0343286927
## EPL_AGE65 0.187412295 0.172071526 -0.1561310891 -0.0773677713
## EPL_AGE17 -0.223949671 -0.213982220 0.1285449080 0.0143361951
## EPL_DISABL -0.015979697 -0.007078403 -0.1871168952 -0.1021251694
## EPL_LIMENG -0.139493059 -0.135824397 0.1568891225 0.0451873965
## SPL_SVM_DOM3 -0.089017173 -0.086265553 -0.0713826647 -0.0889751383
## RPL_SVM_DOM3 -0.102529857 -0.103248008 -0.0474611199 -0.0677111582
## EPL_MOBILE 0.093427886 0.096149178 0.0602221139 0.0068225007
## EPL_GROUPQ -0.226952811 -0.219195284 0.1111745432 -0.0232508456
## SPL_SVM_DOM4 -0.150341746 -0.142327270 0.1251748883 -0.0167386899
## RPL_SVM_DOM4 -0.149956406 -0.142522814 0.1230468641 -0.0055910045
## SPL_SVM -0.181437230 -0.168538236 0.2732236815 -0.0005663096
## RPL_SVM -0.175000969 -0.164255111 0.2925310815 0.0066479703
## F_BPHIGH 0.041498900 0.045201643 0.0951663254 0.0418985036
## F_ASTHMA -0.049979951 -0.037525660 0.2861420072 0.0749334947
## F_CANCER 0.127041735 0.122624268 -0.0506351820 -0.0962142336
## F_MHLTH -0.192052122 -0.180534782 0.1810234682 0.0258228713
## F_DIABETES -0.059011709 -0.042627358 0.3142787153 0.0563966425
## F_HVM -0.066713634 -0.052169591 0.2951364650 0.0458305588
## RPL_HVM -0.066713634 -0.052169591 0.2951364650 0.0458305588
## E_OZONE 0.172657040 0.156582170 -0.3317833860 -0.0726290956
## E_PM 0.101475640 0.092234813 0.5678931502 0.2144641700
## E_DSLPM -0.133569453 -0.125954956 0.2106224046 0.0972826432
## E_TOTCR -0.226759788 -0.214063718 0.2235819885 0.1262038810
## E_NPL NA NA NA NA
## E_TRI -0.247959001 -0.238715020 0.1688726508 -0.0044563693
## E_TSD -0.049929962 -0.060644622 0.0121470949 -0.0051296945
## E_RMP 0.140762129 0.140731038 0.0735972377 -0.0382578163
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK -0.100204590 -0.108892696 0.4036884572 0.6442295946
## E_HOUAGE 0.838897768 0.781416145 0.0324017855 0.1482528403
## E_WLKIND -0.663036172 -0.692118442 0.0525332681 0.0733929824
## E_RAIL -0.021421010 -0.020773412 0.9825606595 0.2321240507
## E_ROAD 0.039863419 0.009945518 0.2088802288 0.9866322350
## E_AIRPRT 0.003362697 -0.001980974 -0.0073494118 -0.2534010247
## E_IMPWTR -0.089363822 -0.076811157 0.2480418549 0.3863714739
## EP_MINRTY -0.098110592 -0.079356606 0.2455539611 0.0432141662
## EP_POV200 -0.160474043 -0.143165814 0.2400838113 0.0152552614
## EP_NOHSDP -0.122721074 -0.121693450 0.2156711138 0.0753201406
## EP_UNEMP 0.010151329 0.022783567 0.1495390316 0.0016237766
## EP_RENTER -0.098319500 -0.088902970 0.3187566732 0.0737812258
## EP_HOUBDN -0.089087788 -0.078325270 0.2917053280 0.0374750812
## EP_UNINSUR -0.048655470 -0.049572536 0.2247331535 0.0199489283
## EP_NOINT -0.131820188 -0.130056288 0.1612874242 -0.0039320194
## EP_AGE65 0.197855550 0.187357397 -0.1072427031 -0.0449074793
## EP_AGE17 -0.201950494 -0.192702233 0.1142019152 0.0125814695
## EP_DISABL 0.046868693 0.058722874 -0.1623750581 -0.0766596544
## EP_LIMENG -0.025854129 -0.023001059 0.2148696185 0.0694345544
## EP_MOBILE 0.081340156 0.077296115 0.0410933559 -0.0085633010
## EP_GROUPQ -0.041139690 -0.038594862 -0.0005683839 0.0151211265
## EP_BPHIGH 0.072842072 0.084283381 0.1470168019 -0.0058469689
## EP_ASTHMA -0.089174274 -0.081311006 0.2375822851 0.0440671099
## EP_CANCER 0.192854436 0.178849666 -0.1874508878 -0.0467420233
## EP_MHLTH -0.162173224 -0.155728327 0.2215591860 0.0417640101
## EP_DIABETES -0.062846585 -0.053610275 0.2102887166 0.0196435957
## EPL_BPHIGH 0.046294334 0.053700478 0.1650957876 0.0055121905
## EPL_ASTHMA -0.105929271 -0.094094858 0.2737632750 0.0732419209
## EPL_CANCER 0.191410960 0.176815432 -0.2088564595 -0.0653142222
## EPL_DIABETES -0.067162918 -0.053698937 0.2647991438 0.0481931985
## EPL_MHLTH -0.186877204 -0.178147537 0.2459709984 0.0530883124
## EPL_AIRPRT SPL_EBM_THEME4 RPL_EBM_DOM4 EPL_IMPWTR
## E_TOTPOP -0.0097371705 0.046254624 0.051988494 0.038561491
## M_TOTPOP 0.0276524093 0.044598774 0.045464679 0.052456103
## E_DAYPOP 0.3312159259 0.154156026 0.099983777 -0.021906638
## SPL_EJI 0.0767821058 0.414960061 0.419059170 0.513525204
## RPL_EJI 0.0628077969 0.478998831 0.488494966 0.521641736
## SPL_SER 0.1200775475 0.479474242 0.480442573 0.587422618
## RPL_SER 0.0835276266 0.521156140 0.527616878 0.591646197
## EPL_OZONE 0.0189894942 -0.222799022 -0.233574412 -0.311642649
## EPL_PM -0.1159571326 0.469657077 0.508653310 0.067437483
## EPL_DSLPM -0.0012008324 0.362562241 0.353549505 0.670209666
## EPL_TOTCR 0.0753759915 0.354059331 0.336444966 0.656314273
## SPL_EBM_THEME1 0.0549009161 0.323864665 0.304457000 0.435784578
## RPL_EBM_DOM1 0.0609411689 0.298399670 0.278615945 0.414863221
## EPL_NPL NA NA NA NA
## EPL_TRI 0.0731800870 0.156414658 0.150557671 0.261574097
## EPL_TSD -0.0052781575 0.005817259 0.006075548 0.030023915
## EPL_RMP 0.2128425221 0.153786302 0.131134117 -0.059233560
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.2483836019 0.280263497 0.255643154 0.205666505
## RPL_EBM_DOM2 0.1845865402 0.268440747 0.252253575 0.208617102
## EPL_PARK -0.0073555061 -0.545768645 -0.525614017 -0.380246308
## EPL_HOUAGE -0.0107492802 0.070050210 0.071303191 -0.105457318
## EPL_WLKIND 0.0881845204 -0.025451388 -0.030171145 0.008389617
## SPL_EBM_THEME3 0.0391949295 0.005487987 0.005120361 -0.098564395
## RPL_EBM_DOM3 0.0384673471 -0.002344521 -0.003026523 -0.084239776
## EPL_RAIL -0.0131136129 0.904714734 0.950821237 0.233769602
## EPL_ROAD -0.5152649739 0.270062966 0.296111909 0.262814663
## EPL_AIRPRT 1.0000000000 0.318416394 0.199782836 0.038677566
## SPL_EBM_THEME4 0.3184163941 1.000000000 0.987883516 0.299684616
## RPL_EBM_DOM4 0.1997828359 0.987883516 1.000000000 0.286260470
## EPL_IMPWTR 0.0386775655 0.299684616 0.286260470 1.000000000
## SPL_EBM_THEME5 0.0386775655 0.299684616 0.286260470 1.000000000
## RPL_EBM_DOM5 0.0386433267 0.299765900 0.286346658 0.999999557
## SPL_EBM 0.3130613707 0.590082394 0.564927976 0.336408874
## RPL_EBM 0.1640215634 0.649635697 0.645301114 0.379404641
## EPL_MINRTY 0.0537513447 0.225326787 0.226996274 0.594612164
## SPL_SVM_DOM1 0.0537513447 0.225326787 0.226996274 0.594612164
## RPL_SVM_DOM1 0.0537513447 0.225326787 0.226996274 0.594612164
## EPL_POV200 0.0557187283 0.260130488 0.259541100 0.594953539
## EPL_NOHSDP 0.0356642958 0.226883858 0.223831984 0.594456046
## EPL_UNEMP 0.0645032189 0.147886665 0.148959421 0.265252223
## EPL_RENTER 0.0048785196 0.300606743 0.308501022 0.429836124
## EPL_HOUBDN 0.0365915229 0.269416481 0.277304011 0.576895356
## EPL_UNINSUR 0.0378656738 0.226629758 0.236725641 0.393687432
## EPL_NOINT 0.0652935423 0.194521265 0.191434947 0.304220976
## SPL_SVM_DOM2 0.0591806242 0.299291164 0.302874206 0.580606654
## RPL_SVM_DOM2 0.0539645839 0.303993507 0.309493925 0.586961557
## EPL_AGE65 0.0425666246 -0.134101060 -0.137261455 -0.525643173
## EPL_AGE17 0.0118783632 0.117644341 0.119380421 0.426489479
## EPL_DISABL 0.0105524321 -0.183910890 -0.191741571 0.021016797
## EPL_LIMENG 0.0375221435 0.164073404 0.162322810 0.468508959
## SPL_SVM_DOM3 0.0586888434 -0.059286009 -0.065397035 0.110824847
## RPL_SVM_DOM3 0.0341289134 -0.044642663 -0.049082954 0.128580972
## EPL_MOBILE 0.0647012146 0.084567739 0.076730275 -0.007338135
## EPL_GROUPQ 0.0296882088 0.099773360 0.096632653 -0.043178296
## SPL_SVM_DOM4 0.0570643835 0.127176719 0.120657249 -0.040812158
## RPL_SVM_DOM4 0.0558535397 0.128439312 0.120282191 -0.050632167
## SPL_SVM 0.0814465772 0.267883976 0.267321405 0.513686732
## RPL_SVM 0.0696453371 0.280447259 0.283514025 0.528014577
## F_BPHIGH -0.0169046047 0.084519883 0.085856035 -0.016153863
## F_ASTHMA 0.0404563112 0.282885936 0.288812874 0.511140317
## F_CANCER -0.0313723573 -0.089170207 -0.079654943 -0.479589132
## F_MHLTH 0.0250564775 0.171654168 0.169155049 0.398603538
## F_DIABETES 0.0465044957 0.303279950 0.310004156 0.437247157
## F_HVM 0.0234354368 0.272414090 0.278345955 0.342229981
## RPL_HVM 0.0234354368 0.272414090 0.278345955 0.342229981
## E_OZONE -0.0060693668 -0.303040127 -0.313043063 -0.367945693
## E_PM -0.1165280999 0.484973211 0.524561962 0.077584569
## E_DSLPM -0.0202523926 0.197081966 0.200901657 0.548460403
## E_TOTCR 0.0768487032 0.265615331 0.253351213 0.597540232
## E_NPL NA NA NA NA
## E_TRI 0.0818575508 0.179911116 0.174926106 0.296043510
## E_TSD -0.0052781575 0.005817259 0.006075548 0.030023915
## E_RMP 0.1817841454 0.139242204 0.112633307 -0.045751775
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.0072409635 0.550009416 0.527299069 0.390603779
## E_HOUAGE -0.0069078029 0.071920948 0.072984866 -0.107718561
## E_WLKIND -0.0880445530 0.023900072 0.028160339 -0.008387480
## E_RAIL -0.0133328717 0.887423579 0.932417418 0.222472698
## E_ROAD -0.6107721479 0.192047816 0.230782285 0.217957780
## E_AIRPRT 0.6967118001 0.257784521 0.142780963 0.032995082
## E_IMPWTR 0.0363838780 0.350744054 0.330345580 0.964509935
## EP_MINRTY 0.0520008610 0.244476051 0.246800228 0.603605225
## EP_POV200 0.0608058506 0.235178001 0.231240594 0.528188603
## EP_NOHSDP 0.0181648728 0.213231828 0.214361551 0.501938221
## EP_UNEMP 0.0413020173 0.145618396 0.149535452 0.255942547
## EP_RENTER 0.0033093970 0.291193863 0.297564798 0.483602366
## EP_HOUBDN 0.0226024972 0.266415927 0.273790985 0.505527053
## EP_UNINSUR 0.0252307672 0.206227649 0.215562806 0.357324485
## EP_NOINT 0.0610101970 0.163394217 0.157735648 0.266850911
## EP_AGE65 0.0238455619 -0.092106544 -0.092902584 -0.528172451
## EP_AGE17 -0.0002123141 0.099111746 0.102391020 0.368233238
## EP_DISABL 0.0003691784 -0.160061711 -0.166341955 0.017331799
## EP_LIMENG 0.0180877225 0.210605591 0.214800524 0.466531748
## EP_MOBILE 0.0837409606 0.073087897 0.061423859 -0.083952706
## EP_GROUPQ 0.0169751492 0.012904739 0.006637975 -0.138469318
## EP_BPHIGH -0.0193583308 0.110904273 0.116794798 0.032383417
## EP_ASTHMA 0.0039535934 0.214213706 0.217379961 0.357064552
## EP_CANCER -0.0583653239 -0.200402409 -0.196688790 -0.624860386
## EP_MHLTH 0.0434666764 0.219773612 0.216282439 0.504304851
## EP_DIABETES 0.0280416308 0.195496359 0.196072548 0.374117671
## EPL_BPHIGH -0.0141298341 0.132268438 0.139145500 0.066083891
## EPL_ASTHMA 0.0181652837 0.260935624 0.264348021 0.520938569
## EPL_CANCER -0.0564630464 -0.223343298 -0.220362948 -0.627877351
## EPL_DIABETES 0.0418593350 0.257083843 0.259911802 0.498724943
## EPL_MHLTH 0.0408311631 0.242488645 0.240112578 0.562673191
## SPL_EBM_THEME5 RPL_EBM_DOM5 SPL_EBM RPL_EBM
## E_TOTPOP 0.038561491 0.038492890 0.108808769 0.114522869
## M_TOTPOP 0.052456103 0.052380312 0.084001096 0.080443471
## E_DAYPOP -0.021906638 -0.021988926 0.215084797 0.147715784
## SPL_EJI 0.513525204 0.513531704 0.341508796 0.389062710
## RPL_EJI 0.521641736 0.521661366 0.368912381 0.429100559
## SPL_SER 0.587422618 0.587431882 0.533243815 0.571784499
## RPL_SER 0.591646197 0.591668966 0.530840615 0.589087671
## EPL_OZONE -0.311642649 -0.311708513 -0.111793693 -0.136051657
## EPL_PM 0.067437483 0.067749081 0.114761735 0.175762632
## EPL_DSLPM 0.670209666 0.670262476 0.287073460 0.365453091
## EPL_TOTCR 0.656314273 0.656292513 0.351539553 0.411997318
## SPL_EBM_THEME1 0.435784578 0.435806651 0.315671680 0.386721353
## RPL_EBM_DOM1 0.414863221 0.414885111 0.301810480 0.368554789
## EPL_NPL NA NA NA NA
## EPL_TRI 0.261574097 0.261440115 0.438397104 0.462606186
## EPL_TSD 0.030023915 0.029970495 0.179323047 0.095583924
## EPL_RMP -0.059233560 -0.059203726 0.424801387 0.343380872
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.205666505 0.205555551 0.802500753 0.745957573
## RPL_EBM_DOM2 0.208617102 0.208500161 0.784181164 0.760511832
## EPL_PARK -0.380246308 -0.380289441 -0.312747835 -0.413419241
## EPL_HOUAGE -0.105457318 -0.105282314 0.298991840 0.284761977
## EPL_WLKIND 0.008389617 0.008357429 0.263738112 0.212188725
## SPL_EBM_THEME3 -0.098564395 -0.098452283 0.349459606 0.304579602
## RPL_EBM_DOM3 -0.084239776 -0.084141029 0.341447029 0.293658956
## EPL_RAIL 0.233769602 0.233847476 0.476822989 0.576991103
## EPL_ROAD 0.262814663 0.262917214 0.114101226 0.268172062
## EPL_AIRPRT 0.038677566 0.038643327 0.313061371 0.164021563
## SPL_EBM_THEME4 0.299684616 0.299765900 0.590082394 0.649635697
## RPL_EBM_DOM4 0.286260470 0.286346658 0.564927976 0.645301114
## EPL_IMPWTR 1.000000000 0.999999557 0.336408874 0.379404641
## SPL_EBM_THEME5 1.000000000 0.999999557 0.336408874 0.379404641
## RPL_EBM_DOM5 0.999999557 1.000000000 0.336405376 0.379414873
## SPL_EBM 0.336408874 0.336405376 1.000000000 0.967245811
## RPL_EBM 0.379404641 0.379414873 0.967245811 1.000000000
## EPL_MINRTY 0.594612164 0.594554336 0.179228876 0.218688845
## SPL_SVM_DOM1 0.594612164 0.594554336 0.179228876 0.218688845
## RPL_SVM_DOM1 0.594612164 0.594554336 0.179228876 0.218688845
## EPL_POV200 0.594953539 0.594949665 0.240347040 0.273213446
## EPL_NOHSDP 0.594456046 0.594438785 0.195639036 0.239916029
## EPL_UNEMP 0.265252223 0.265212546 0.114915772 0.123012560
## EPL_RENTER 0.429836124 0.429900022 0.245530620 0.276971882
## EPL_HOUBDN 0.576895356 0.576928719 0.229967298 0.260788185
## EPL_UNINSUR 0.393687432 0.393710393 0.165508416 0.179757959
## EPL_NOINT 0.304220976 0.304205445 0.069124963 0.093427650
## SPL_SVM_DOM2 0.580606654 0.580611437 0.231395655 0.264642152
## RPL_SVM_DOM2 0.586961557 0.586973208 0.240034237 0.275771174
## EPL_AGE65 -0.525643173 -0.525646596 -0.109994247 -0.141244701
## EPL_AGE17 0.426489479 0.426425515 0.061547157 0.089428511
## EPL_DISABL 0.021016797 0.021007641 -0.090879852 -0.111484047
## EPL_LIMENG 0.468508959 0.468518354 0.194320829 0.221926685
## SPL_SVM_DOM3 0.110824847 0.110772237 -0.019853443 -0.024081821
## RPL_SVM_DOM3 0.128580972 0.128525402 -0.014149764 -0.016850921
## EPL_MOBILE -0.007338135 -0.007251370 0.056782288 0.051571026
## EPL_GROUPQ -0.043178296 -0.043169518 -0.026278443 -0.025788765
## SPL_SVM_DOM4 -0.040812158 -0.040762403 0.004938935 0.002827738
## RPL_SVM_DOM4 -0.050632167 -0.050596206 0.007071500 0.004473238
## SPL_SVM 0.513686732 0.513685136 0.188491474 0.215620909
## RPL_SVM 0.528014577 0.528021023 0.203514852 0.234676586
## F_BPHIGH -0.016153863 -0.016154026 -0.035091843 -0.010181763
## F_ASTHMA 0.511140317 0.511158495 0.165931657 0.202947478
## F_CANCER -0.479589132 -0.479607615 -0.079044525 -0.103775182
## F_MHLTH 0.398603538 0.398597201 0.091064999 0.121762424
## F_DIABETES 0.437247157 0.437261004 0.151774837 0.202560469
## F_HVM 0.342229981 0.342232740 0.104951736 0.150281065
## RPL_HVM 0.342229981 0.342232740 0.104951736 0.150281065
## E_OZONE -0.367945693 -0.368063106 -0.150902101 -0.179642260
## E_PM 0.077584569 0.077893195 0.123668093 0.186908698
## E_DSLPM 0.548460403 0.548565460 0.171530278 0.220133188
## E_TOTCR 0.597540232 0.597522518 0.307451347 0.344531263
## E_NPL NA NA NA NA
## E_TRI 0.296043510 0.295915035 0.440430505 0.458185312
## E_TSD 0.030023915 0.029970495 0.179323047 0.095583924
## E_RMP -0.045751775 -0.045715330 0.354122288 0.290561894
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.390603779 0.390650918 0.315631028 0.419074057
## E_HOUAGE -0.107718561 -0.107543088 0.298169934 0.284599175
## E_WLKIND -0.008387480 -0.008348928 -0.265853908 -0.215599307
## E_RAIL 0.222472698 0.222557343 0.460084564 0.552527315
## E_ROAD 0.217957780 0.218058541 0.061381369 0.216303328
## E_AIRPRT 0.032995082 0.032945014 0.224415683 0.114129722
## E_IMPWTR 0.964509935 0.964568138 0.350258615 0.406407756
## EP_MINRTY 0.603605225 0.603551054 0.197019637 0.237896620
## EP_POV200 0.528188603 0.528168626 0.219969874 0.247593993
## EP_NOHSDP 0.501938221 0.501894201 0.179415734 0.221812267
## EP_UNEMP 0.255942547 0.255858372 0.115067258 0.118962964
## EP_RENTER 0.483602366 0.483671111 0.253801984 0.286299757
## EP_HOUBDN 0.505527053 0.505577575 0.207430976 0.230590189
## EP_UNINSUR 0.357324485 0.357338618 0.161244776 0.174935622
## EP_NOINT 0.266850911 0.266825739 0.070604669 0.092370725
## EP_AGE65 -0.528172451 -0.528167242 -0.100740715 -0.124100681
## EP_AGE17 0.368233238 0.368177306 0.031715828 0.061189161
## EP_DISABL 0.017331799 0.017327423 -0.024960704 -0.051686906
## EP_LIMENG 0.466531748 0.466601054 0.240161818 0.267309248
## EP_MOBILE -0.083952706 -0.083858511 0.025830401 0.019352020
## EP_GROUPQ -0.138469318 -0.138446061 -0.001667717 -0.018686644
## EP_BPHIGH 0.032383417 0.032343895 -0.026078824 0.004356150
## EP_ASTHMA 0.357064552 0.357028512 0.055526193 0.096253707
## EP_CANCER -0.624860386 -0.624862314 -0.209699184 -0.229591960
## EP_MHLTH 0.504304851 0.504275398 0.170248386 0.201932345
## EP_DIABETES 0.374117671 0.374051715 0.145850895 0.186601223
## EPL_BPHIGH 0.066083891 0.066053752 -0.022415989 0.014867519
## EPL_ASTHMA 0.520938569 0.520955530 0.137600982 0.181334320
## EPL_CANCER -0.627877351 -0.627882597 -0.198325266 -0.224213981
## EPL_DIABETES 0.498724943 0.498694668 0.187594427 0.236777264
## EPL_MHLTH 0.562673191 0.562672374 0.175795809 0.209418399
## EPL_MINRTY SPL_SVM_DOM1 RPL_SVM_DOM1 EPL_POV200 EPL_NOHSDP
## E_TOTPOP 0.214363665 0.214363665 0.214363665 0.20209000 0.140459315
## M_TOTPOP 0.262441712 0.262441712 0.262441712 0.24344048 0.202449846
## E_DAYPOP 0.017797712 0.017797712 0.017797712 0.10840202 0.009897681
## SPL_EJI 0.707582693 0.707582693 0.707582693 0.82897933 0.771515954
## RPL_EJI 0.711102717 0.711102717 0.711102717 0.80915176 0.763078484
## SPL_SER 0.647770758 0.647770758 0.647770758 0.86132762 0.798786606
## RPL_SER 0.640529321 0.640529321 0.640529321 0.83322652 0.785237825
## EPL_OZONE -0.269531058 -0.269531058 -0.269531058 -0.46577561 -0.330787311
## EPL_PM 0.106143293 0.106143293 0.106143293 0.14579104 0.079814128
## EPL_DSLPM 0.465308707 0.465308707 0.465308707 0.58543784 0.540909562
## EPL_TOTCR 0.463098719 0.463098719 0.463098719 0.60825273 0.550963060
## SPL_EBM_THEME1 0.261310406 0.261310406 0.261310406 0.19019498 0.276663542
## RPL_EBM_DOM1 0.246182348 0.246182348 0.246182348 0.16984920 0.261787681
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.194064392 0.194064392 0.194064392 0.18635739 0.191592255
## EPL_TSD -0.003576159 -0.003576159 -0.003576159 0.02311185 -0.013706500
## EPL_RMP -0.101723260 -0.101723260 -0.101723260 0.03991028 -0.031488784
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.100530258 0.100530258 0.100530258 0.21573427 0.155771639
## RPL_EBM_DOM2 0.119063218 0.119063218 0.119063218 0.23285199 0.178389995
## EPL_PARK -0.164898023 -0.164898023 -0.164898023 -0.14663047 -0.189302928
## EPL_HOUAGE -0.208600232 -0.208600232 -0.208600232 -0.25719687 -0.228682769
## EPL_WLKIND 0.118270447 0.118270447 0.118270447 0.06162915 0.041548493
## SPL_EBM_THEME3 -0.103686841 -0.103686841 -0.103686841 -0.16995540 -0.161922496
## RPL_EBM_DOM3 -0.085137599 -0.085137599 -0.085137599 -0.15485251 -0.160967796
## EPL_RAIL 0.225172355 0.225172355 0.225172355 0.26440381 0.212358291
## EPL_ROAD 0.033880502 0.033880502 0.033880502 0.03740926 0.098937616
## EPL_AIRPRT 0.053751345 0.053751345 0.053751345 0.05571873 0.035664296
## SPL_EBM_THEME4 0.225326787 0.225326787 0.225326787 0.26013049 0.226883858
## RPL_EBM_DOM4 0.226996274 0.226996274 0.226996274 0.25954110 0.223831984
## EPL_IMPWTR 0.594612164 0.594612164 0.594612164 0.59495354 0.594456046
## SPL_EBM_THEME5 0.594612164 0.594612164 0.594612164 0.59495354 0.594456046
## RPL_EBM_DOM5 0.594554336 0.594554336 0.594554336 0.59494966 0.594438785
## SPL_EBM 0.179228876 0.179228876 0.179228876 0.24034704 0.195639036
## RPL_EBM 0.218688845 0.218688845 0.218688845 0.27321345 0.239916029
## EPL_MINRTY 1.000000000 1.000000000 1.000000000 0.69662372 0.673881206
## SPL_SVM_DOM1 1.000000000 1.000000000 1.000000000 0.69662372 0.673881206
## RPL_SVM_DOM1 1.000000000 1.000000000 1.000000000 0.69662372 0.673881206
## EPL_POV200 0.696623718 0.696623718 0.696623718 1.00000000 0.831408763
## EPL_NOHSDP 0.673881206 0.673881206 0.673881206 0.83140876 1.000000000
## EPL_UNEMP 0.362535955 0.362535955 0.362535955 0.47869788 0.393768423
## EPL_RENTER 0.442515939 0.442515939 0.442515939 0.78536533 0.656753989
## EPL_HOUBDN 0.691474009 0.691474009 0.691474009 0.83796417 0.745653933
## EPL_UNINSUR 0.351621456 0.351621456 0.351621456 0.47155497 0.459168211
## EPL_NOINT 0.463882172 0.463882172 0.463882172 0.58718105 0.545796980
## SPL_SVM_DOM2 0.678680860 0.678680860 0.678680860 0.92313022 0.844890734
## RPL_SVM_DOM2 0.690746001 0.690746001 0.690746001 0.91795438 0.850799380
## EPL_AGE65 -0.585353391 -0.585353391 -0.585353391 -0.67875453 -0.598551503
## EPL_AGE17 0.559791905 0.559791905 0.559791905 0.73168208 0.617196950
## EPL_DISABL 0.042604176 0.042604176 0.042604176 0.14665946 0.145383315
## EPL_LIMENG 0.487361893 0.487361893 0.487361893 0.65648407 0.672470508
## SPL_SVM_DOM3 0.186522659 0.186522659 0.186522659 0.36564141 0.342555749
## RPL_SVM_DOM3 0.195527844 0.195527844 0.195527844 0.38257759 0.361549654
## EPL_MOBILE -0.039199048 -0.039199048 -0.039199048 -0.03931265 -0.003813159
## EPL_GROUPQ -0.019050662 -0.019050662 -0.019050662 0.11912513 0.089823502
## SPL_SVM_DOM4 -0.035490200 -0.035490200 -0.035490200 0.08364164 0.075625706
## RPL_SVM_DOM4 -0.050719570 -0.050719570 -0.050719570 0.07079732 0.069968569
## SPL_SVM 0.645745423 0.645745423 0.645745423 0.88685113 0.816713929
## RPL_SVM 0.670686731 0.670686731 0.670686731 0.89957996 0.840221459
## F_BPHIGH 0.284409899 0.284409899 0.284409899 0.09065931 0.127034051
## F_ASTHMA 0.677392740 0.677392740 0.677392740 0.67821972 0.633185374
## F_CANCER -0.670668506 -0.670668506 -0.670668506 -0.56371004 -0.565089856
## F_MHLTH 0.500000056 0.500000056 0.500000056 0.74505176 0.648372559
## F_DIABETES 0.729598964 0.729598964 0.729598964 0.63077328 0.626594472
## F_HVM 0.610576209 0.610576209 0.610576209 0.62723811 0.586197689
## RPL_HVM 0.610576209 0.610576209 0.610576209 0.62723811 0.586197689
## E_OZONE -0.287111691 -0.287111691 -0.287111691 -0.52555980 -0.364654890
## E_PM 0.115456224 0.115456224 0.115456224 0.15360946 0.088276924
## E_DSLPM 0.434772054 0.434772054 0.434772054 0.56163980 0.498760090
## E_TOTCR 0.458027620 0.458027620 0.458027620 0.61461211 0.538218976
## E_NPL NA NA NA NA NA
## E_TRI 0.229017568 0.229017568 0.229017568 0.21592552 0.226367937
## E_TSD -0.003576159 -0.003576159 -0.003576159 0.02311185 -0.013706500
## E_RMP -0.062782330 -0.062782330 -0.062782330 0.06414709 0.019654147
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.161626471 0.161626471 0.161626471 0.14422675 0.188884207
## E_HOUAGE -0.204085839 -0.204085839 -0.204085839 -0.24908523 -0.216390227
## E_WLKIND -0.122066268 -0.122066268 -0.122066268 -0.06702901 -0.043806095
## E_RAIL 0.224978365 0.224978365 0.224978365 0.26530986 0.215402333
## E_ROAD 0.016591350 0.016591350 0.016591350 0.01957189 0.078193343
## E_AIRPRT 0.031752797 0.031752797 0.031752797 0.05282176 0.042725974
## E_IMPWTR 0.556042000 0.556042000 0.556042000 0.53577398 0.559992501
## EP_MINRTY 0.995594477 0.995594477 0.995594477 0.69938991 0.671810519
## EP_POV200 0.622923193 0.622923193 0.622923193 0.96263653 0.789297703
## EP_NOHSDP 0.590115160 0.590115160 0.590115160 0.81515776 0.890107652
## EP_UNEMP 0.346038596 0.346038596 0.346038596 0.48533263 0.353634146
## EP_RENTER 0.511884310 0.511884310 0.511884310 0.85533997 0.705953703
## EP_HOUBDN 0.580522652 0.580522652 0.580522652 0.80250224 0.654247660
## EP_UNINSUR 0.317269945 0.317269945 0.317269945 0.44665523 0.426184178
## EP_NOINT 0.433111048 0.433111048 0.433111048 0.55550564 0.514806814
## EP_AGE65 -0.590787541 -0.590787541 -0.590787541 -0.63219898 -0.578548447
## EP_AGE17 0.528419225 0.528419225 0.528419225 0.65975683 0.578912918
## EP_DISABL -0.025182863 -0.025182863 -0.025182863 0.14128207 0.094571460
## EP_LIMENG 0.441997026 0.441997026 0.441997026 0.65725930 0.622966778
## EP_MOBILE -0.050243001 -0.050243001 -0.050243001 -0.08988080 -0.036703027
## EP_GROUPQ -0.261281882 -0.261281882 -0.261281882 -0.05723070 -0.080854419
## EP_BPHIGH 0.333833539 0.333833539 0.333833539 0.13959437 0.169073375
## EP_ASTHMA 0.651027883 0.651027883 0.651027883 0.64729779 0.612624578
## EP_CANCER -0.703562622 -0.703562622 -0.703562622 -0.72975481 -0.644241120
## EP_MHLTH 0.625399785 0.625399785 0.625399785 0.87027912 0.789572011
## EP_DIABETES 0.627575221 0.627575221 0.627575221 0.69063138 0.640517316
## EPL_BPHIGH 0.378010365 0.378010365 0.378010365 0.17514835 0.208937173
## EPL_ASTHMA 0.765834831 0.765834831 0.765834831 0.73638934 0.730160830
## EPL_CANCER -0.751935026 -0.751935026 -0.751935026 -0.75268485 -0.677927071
## EPL_DIABETES 0.792426636 0.792426636 0.792426636 0.73677575 0.726339029
## EPL_MHLTH 0.663503459 0.663503459 0.663503459 0.91677950 0.827531193
## EPL_UNEMP EPL_RENTER EPL_HOUBDN EPL_UNINSUR EPL_NOINT
## E_TOTPOP 0.138645725 0.22473590 0.072982701 0.1754054019 0.134519359
## M_TOTPOP 0.176468974 0.24720507 0.153358948 0.2202675408 0.164350897
## E_DAYPOP 0.097365607 0.15597205 0.012455246 0.0522941030 0.064211504
## SPL_EJI 0.464080469 0.67935050 0.695002091 0.4190006061 0.649882575
## RPL_EJI 0.440172547 0.67288289 0.714209929 0.4335493785 0.613442157
## SPL_SER 0.515248585 0.74619829 0.775241966 0.5202083149 0.589659623
## RPL_SER 0.485275325 0.73429076 0.781127602 0.5026575086 0.566484137
## EPL_OZONE -0.228971056 -0.42636902 -0.279374047 -0.2422174915 -0.319828304
## EPL_PM 0.167913548 0.21453205 0.124128729 0.2097884953 0.070246274
## EPL_DSLPM 0.263959955 0.49056981 0.462721889 0.2696207383 0.350367247
## EPL_TOTCR 0.240763697 0.48801137 0.468451472 0.2620604561 0.362551627
## SPL_EBM_THEME1 0.066084342 0.12482920 0.259412598 0.0863247721 0.051610189
## RPL_EBM_DOM1 0.056415727 0.10360466 0.247894011 0.0727031121 0.044517064
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.001741317 0.09568004 0.118651030 0.0366510856 0.178431465
## EPL_TSD 0.030818032 0.02929490 0.014304780 0.0776121643 -0.037523117
## EPL_RMP 0.048348153 0.10627577 0.050127733 0.0711802768 -0.127109679
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.046485180 0.18519733 0.158061682 0.1055835074 0.059558973
## RPL_EBM_DOM2 0.044955393 0.20115914 0.170064865 0.1010228341 0.065754903
## EPL_PARK -0.061832330 -0.14762371 -0.082098188 -0.0494791570 -0.079235641
## EPL_HOUAGE -0.071443587 -0.14343997 -0.163768879 -0.0776280552 -0.277261166
## EPL_WLKIND 0.113160601 0.04978442 0.028635873 -0.0141648404 0.101048899
## SPL_EBM_THEME3 0.003514276 -0.09049482 -0.113268950 -0.0693675865 -0.159604957
## RPL_EBM_DOM3 0.017694135 -0.08337381 -0.100655151 -0.0691673415 -0.154224629
## EPL_RAIL 0.146113594 0.32592137 0.293414878 0.2491910032 0.200576550
## EPL_ROAD -0.018054196 0.08194982 0.020979398 0.0007849773 -0.015349949
## EPL_AIRPRT 0.064503219 0.00487852 0.036591523 0.0378656738 0.065293542
## SPL_EBM_THEME4 0.147886665 0.30060674 0.269416481 0.2266297579 0.194521265
## RPL_EBM_DOM4 0.148959421 0.30850102 0.277304011 0.2367256409 0.191434947
## EPL_IMPWTR 0.265252223 0.42983612 0.576895356 0.3936874318 0.304220976
## SPL_EBM_THEME5 0.265252223 0.42983612 0.576895356 0.3936874318 0.304220976
## RPL_EBM_DOM5 0.265212546 0.42990002 0.576928719 0.3937103930 0.304205445
## SPL_EBM 0.114915772 0.24553062 0.229967298 0.1655084159 0.069124963
## RPL_EBM 0.123012560 0.27697188 0.260788185 0.1797579589 0.093427650
## EPL_MINRTY 0.362535955 0.44251594 0.691474009 0.3516214556 0.463882172
## SPL_SVM_DOM1 0.362535955 0.44251594 0.691474009 0.3516214556 0.463882172
## RPL_SVM_DOM1 0.362535955 0.44251594 0.691474009 0.3516214556 0.463882172
## EPL_POV200 0.478697882 0.78536533 0.837964171 0.4715549658 0.587181050
## EPL_NOHSDP 0.393768423 0.65675399 0.745653933 0.4591682109 0.545796980
## EPL_UNEMP 1.000000000 0.35243872 0.456482652 0.3506877542 0.246559548
## EPL_RENTER 0.352438719 1.00000000 0.680740661 0.4384297429 0.541880743
## EPL_HOUBDN 0.456482652 0.68074066 1.000000000 0.4704867366 0.476142325
## EPL_UNINSUR 0.350687754 0.43842974 0.470486737 1.0000000000 0.236966661
## EPL_NOINT 0.246559548 0.54188074 0.476142325 0.2369666606 1.000000000
## SPL_SVM_DOM2 0.631809319 0.81325970 0.853973869 0.6490451340 0.671244111
## RPL_SVM_DOM2 0.612446035 0.82180017 0.878701856 0.6264423359 0.653180277
## EPL_AGE65 -0.389466620 -0.59158557 -0.632217746 -0.4837254342 -0.365126834
## EPL_AGE17 0.332707533 0.56665630 0.569546767 0.3331097978 0.422948173
## EPL_DISABL 0.065010497 0.08815746 0.043659263 -0.1214214893 0.295321007
## EPL_LIMENG 0.271770883 0.58085532 0.571179405 0.3825637448 0.362887939
## SPL_SVM_DOM3 0.097543127 0.24535190 0.189032261 -0.0405088916 0.347130490
## RPL_SVM_DOM3 0.099428993 0.26461334 0.213528087 0.0153166353 0.321068285
## EPL_MOBILE -0.033385195 -0.04087298 -0.038704892 0.0138132372 0.005202222
## EPL_GROUPQ 0.144151770 0.07169182 0.009981495 0.0668953031 0.110314945
## SPL_SVM_DOM4 0.108110788 0.04196823 -0.010207523 0.0644178983 0.097684171
## RPL_SVM_DOM4 0.106232074 0.02857991 -0.023098823 0.0398918058 0.072609009
## SPL_SVM 0.570393095 0.73700456 0.760335588 0.5336046030 0.673074030
## RPL_SVM 0.556031805 0.76150216 0.803081576 0.5367807451 0.657299992
## F_BPHIGH 0.065320622 -0.01325867 0.031189845 -0.1466114954 0.261688159
## F_ASTHMA 0.337905427 0.55484687 0.673528491 0.4406120370 0.456961344
## F_CANCER -0.311451753 -0.40456527 -0.602610240 -0.3128274849 -0.375106691
## F_MHLTH 0.409711370 0.60162722 0.532348551 0.3498571239 0.602688703
## F_DIABETES 0.293874712 0.49154333 0.566979135 0.3066515369 0.470754173
## F_HVM 0.322707882 0.47932862 0.480178166 0.2440472823 0.565335015
## RPL_HVM 0.322707882 0.47932862 0.480178166 0.2440472823 0.565335015
## E_OZONE -0.271428823 -0.50814598 -0.342271506 -0.2950830941 -0.334158510
## E_PM 0.173237868 0.21998038 0.131676526 0.2168689451 0.078653710
## E_DSLPM 0.256428370 0.47683706 0.448615247 0.2855458081 0.349396779
## E_TOTCR 0.249329728 0.49293273 0.470469851 0.2802386405 0.380678592
## E_NPL NA NA NA NA NA
## E_TRI 0.026682875 0.14910312 0.170265121 0.0857411578 0.199809079
## E_TSD 0.030818032 0.02929490 0.014304780 0.0776121643 -0.037523117
## E_RMP 0.027369736 0.13908913 0.070540769 0.0842256089 -0.125790549
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.060438847 0.14356343 0.081195126 0.0447384605 0.074879329
## E_HOUAGE -0.064479283 -0.13634275 -0.156954656 -0.0727190566 -0.265405142
## E_WLKIND -0.117531919 -0.05214146 -0.030435517 0.0087344221 -0.095453702
## E_RAIL 0.153752636 0.33560345 0.292044171 0.2463046105 0.189323769
## E_ROAD -0.032241031 0.06879574 0.008282391 0.0012190398 -0.026211452
## E_AIRPRT 0.035555076 0.03078723 0.036161091 0.0572379056 0.065676828
## E_IMPWTR 0.249119331 0.38234120 0.536535447 0.3510801480 0.280792444
## EP_MINRTY 0.355215732 0.44719464 0.693796342 0.3653366494 0.466658065
## EP_POV200 0.459654871 0.73754173 0.749919877 0.4060815676 0.565357796
## EP_NOHSDP 0.393297009 0.62691282 0.639646639 0.3979669018 0.562089528
## EP_UNEMP 0.815656456 0.27746879 0.423839650 0.2188733051 0.238810979
## EP_RENTER 0.400236391 0.95292098 0.707977905 0.4559593512 0.536337823
## EP_HOUBDN 0.445624758 0.59971039 0.862606352 0.4023148053 0.375112786
## EP_UNINSUR 0.330618747 0.41397817 0.429272365 0.9684556792 0.220390794
## EP_NOINT 0.203427579 0.49433256 0.423174703 0.1883994317 0.960078452
## EP_AGE65 -0.345450769 -0.56602077 -0.626481160 -0.4697991892 -0.379850241
## EP_AGE17 0.271607643 0.52854004 0.501967728 0.2741928716 0.423640333
## EP_DISABL 0.110003892 0.03755459 0.058055070 -0.1063405587 0.105060550
## EP_LIMENG 0.294802811 0.57952426 0.541213094 0.4765837569 0.335051340
## EP_MOBILE -0.063358742 -0.08019281 -0.092211466 -0.0127607343 -0.005758397
## EP_GROUPQ 0.042320270 -0.09864199 -0.104545528 -0.1561214206 -0.191838994
## EP_BPHIGH 0.088806867 0.01075523 0.053308536 -0.0461257565 0.279097669
## EP_ASTHMA 0.341807397 0.45387290 0.544902077 0.2220889269 0.597730591
## EP_CANCER -0.418045311 -0.57406722 -0.736945509 -0.4730224550 -0.399867940
## EP_MHLTH 0.443065483 0.68902628 0.710994463 0.3904657389 0.638760428
## EP_DIABETES 0.290916631 0.48606573 0.506674390 0.2037325355 0.571126596
## EPL_BPHIGH 0.109919955 0.03818936 0.090262917 -0.0279623113 0.316224058
## EPL_ASTHMA 0.389764985 0.54166907 0.694117345 0.4056460932 0.584994223
## EPL_CANCER -0.423922951 -0.58317066 -0.745288684 -0.4654000694 -0.449385504
## EPL_DIABETES 0.370647717 0.51907834 0.609144086 0.3576593252 0.538840167
## EPL_MHLTH 0.490190160 0.73630850 0.757725732 0.4621002761 0.652908644
## SPL_SVM_DOM2 RPL_SVM_DOM2 EPL_AGE65 EPL_AGE17 EPL_DISABL
## E_TOTPOP 0.20704620 0.19758554 -0.173335833 0.201259174 0.005213395
## M_TOTPOP 0.26489394 0.26218269 -0.200062762 0.221374883 -0.021609776
## E_DAYPOP 0.09763715 0.09068524 -0.031674831 -0.018089749 0.039906069
## SPL_EJI 0.83360159 0.82566629 -0.477124765 0.576262009 0.216310778
## RPL_EJI 0.82041905 0.82357805 -0.465894432 0.548225297 0.152617785
## SPL_SER 0.88839827 0.89065401 -0.527332604 0.604201581 0.187419955
## RPL_SER 0.86417727 0.87767218 -0.502111558 0.562867599 0.153349626
## EPL_OZONE -0.42928298 -0.39003921 0.391017819 -0.380379854 -0.120772288
## EPL_PM 0.19208193 0.18597369 -0.176559738 0.089100861 -0.195053460
## EPL_DSLPM 0.54533162 0.52574069 -0.461396971 0.433066178 0.076654092
## EPL_TOTCR 0.54845281 0.53318474 -0.442117405 0.445243061 0.127887267
## SPL_EBM_THEME1 0.18656350 0.21604980 -0.104919158 0.081650012 -0.087137546
## RPL_EBM_DOM1 0.16821208 0.19780801 -0.087561646 0.065691551 -0.087501348
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.14756382 0.13934683 -0.078087999 0.135760436 0.136819732
## EPL_TSD 0.02584510 0.02855810 -0.068599698 0.048193264 0.018085408
## EPL_RMP 0.02976749 0.04211435 -0.046898770 -0.040367791 -0.189821990
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.17031223 0.17315809 -0.123773238 0.103102526 -0.025524276
## RPL_EBM_DOM2 0.18189209 0.18571445 -0.130091964 0.110710674 -0.030448172
## EPL_PARK -0.13683723 -0.14245833 0.089834113 -0.106389154 0.044155930
## EPL_HOUAGE -0.22674030 -0.21641492 0.231338787 -0.294067411 -0.076803611
## EPL_WLKIND 0.07372879 0.06835455 0.013123094 0.008792870 0.072586798
## SPL_EBM_THEME3 -0.13978887 -0.13524624 0.187412295 -0.223949671 -0.015979697
## RPL_EBM_DOM3 -0.12890741 -0.12424127 0.172071526 -0.213982220 -0.007078403
## EPL_RAIL 0.31125582 0.31932501 -0.156131089 0.128544908 -0.187116895
## EPL_ROAD 0.03256108 0.03432869 -0.077367771 0.014336195 -0.102125169
## EPL_AIRPRT 0.05918062 0.05396458 0.042566625 0.011878363 0.010552432
## SPL_EBM_THEME4 0.29929116 0.30399351 -0.134101060 0.117644341 -0.183910890
## RPL_EBM_DOM4 0.30287421 0.30949393 -0.137261455 0.119380421 -0.191741571
## EPL_IMPWTR 0.58060665 0.58696156 -0.525643173 0.426489479 0.021016797
## SPL_EBM_THEME5 0.58060665 0.58696156 -0.525643173 0.426489479 0.021016797
## RPL_EBM_DOM5 0.58061144 0.58697321 -0.525646596 0.426425515 0.021007641
## SPL_EBM 0.23139566 0.24003424 -0.109994247 0.061547157 -0.090879852
## RPL_EBM 0.26464215 0.27577117 -0.141244701 0.089428511 -0.111484047
## EPL_MINRTY 0.67868086 0.69074600 -0.585353391 0.559791905 0.042604176
## SPL_SVM_DOM1 0.67868086 0.69074600 -0.585353391 0.559791905 0.042604176
## RPL_SVM_DOM1 0.67868086 0.69074600 -0.585353391 0.559791905 0.042604176
## EPL_POV200 0.92313022 0.91795438 -0.678754533 0.731682077 0.146659459
## EPL_NOHSDP 0.84489073 0.85079938 -0.598551503 0.617196950 0.145383315
## EPL_UNEMP 0.63180932 0.61244604 -0.389466620 0.332707533 0.065010497
## EPL_RENTER 0.81325970 0.82180017 -0.591585571 0.566656298 0.088157463
## EPL_HOUBDN 0.85397387 0.87870186 -0.632217746 0.569546767 0.043659263
## EPL_UNINSUR 0.64904513 0.62644234 -0.483725434 0.333109798 -0.121421489
## EPL_NOINT 0.67124411 0.65318028 -0.365126834 0.422948173 0.295321007
## SPL_SVM_DOM2 1.00000000 0.99231556 -0.691997469 0.661324993 0.121995376
## RPL_SVM_DOM2 0.99231556 1.00000000 -0.682330440 0.641313525 0.106977992
## EPL_AGE65 -0.69199747 -0.68233044 1.000000000 -0.682597246 0.135678506
## EPL_AGE17 0.66132499 0.64131352 -0.682597246 1.000000000 0.041781319
## EPL_DISABL 0.12199538 0.10697799 0.135678506 0.041781319 1.000000000
## EPL_LIMENG 0.63961570 0.62882806 -0.494070714 0.525076486 0.073096076
## SPL_SVM_DOM3 0.28319180 0.26281983 0.122794166 0.458960461 0.732633349
## RPL_SVM_DOM3 0.30374820 0.28165121 0.054095845 0.487494383 0.675729633
## EPL_MOBILE -0.02541225 -0.02383217 0.025112884 -0.063741603 -0.019266015
## EPL_GROUPQ 0.12044550 0.09119462 -0.023383819 0.065420147 0.089190089
## SPL_SVM_DOM4 0.09153858 0.06707567 -0.007961078 0.025440306 0.067566561
## RPL_SVM_DOM4 0.07325454 0.04854426 0.009596655 0.016733101 0.062364911
## SPL_SVM 0.92418943 0.90713127 -0.549192770 0.683621165 0.311194421
## RPL_SVM 0.93545071 0.93319538 -0.562276357 0.676301228 0.271435433
## F_BPHIGH 0.07668120 0.07619081 0.140232064 -0.016753641 0.244571310
## F_ASTHMA 0.69506215 0.71820985 -0.530648939 0.454464076 0.051662260
## F_CANCER -0.57559738 -0.59805867 0.611544003 -0.429496517 -0.019503422
## F_MHLTH 0.72365858 0.68314065 -0.579400336 0.613893156 0.165598424
## F_DIABETES 0.62199804 0.62461077 -0.420129382 0.446673701 0.038750921
## F_HVM 0.61158303 0.59654736 -0.333841423 0.431332455 0.195777680
## RPL_HVM 0.61158303 0.59654736 -0.333841423 0.431332455 0.195777680
## E_OZONE -0.49364416 -0.45467548 0.432784901 -0.417337318 -0.089457715
## E_PM 0.20141739 0.19518013 -0.182323388 0.094024997 -0.193527592
## E_DSLPM 0.53076894 0.50812092 -0.457843341 0.425594349 0.090641095
## E_TOTCR 0.55831876 0.53889020 -0.452012996 0.454572888 0.160049943
## E_NPL NA NA NA NA NA
## E_TRI 0.19556154 0.18885603 -0.111922968 0.162220280 0.125937230
## E_TSD 0.02584510 0.02855810 -0.068599698 0.048193264 0.018085408
## E_RMP 0.04964533 0.06392701 -0.046459241 0.002824652 -0.178495616
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.13330473 0.13845473 -0.092165331 0.102211970 -0.048113645
## E_HOUAGE -0.21606521 -0.20636361 0.228025991 -0.288012053 -0.070055629
## E_WLKIND -0.07697893 -0.07118086 -0.011250219 -0.011435374 -0.072213088
## E_RAIL 0.31208529 0.31887617 -0.159355556 0.130579210 -0.194513651
## E_ROAD 0.01626084 0.01789865 -0.073621876 0.002841175 -0.105047266
## E_AIRPRT 0.06136602 0.05126683 -0.040039180 0.027102960 -0.059038197
## E_IMPWTR 0.53111185 0.54147835 -0.476914356 0.376663969 0.029561835
## EP_MINRTY 0.68193893 0.69471889 -0.587461715 0.560806123 0.029878577
## EP_POV200 0.86532033 0.84541812 -0.627577679 0.725615033 0.173197283
## EP_NOHSDP 0.79451210 0.76958656 -0.532000464 0.634897153 0.191022349
## EP_UNEMP 0.54208068 0.50670748 -0.353566889 0.351648183 0.152716853
## EP_RENTER 0.84678590 0.83889705 -0.654070040 0.618614027 0.091150194
## EP_HOUBDN 0.76269059 0.76277645 -0.567489242 0.557226689 0.029323506
## EP_UNINSUR 0.61414230 0.58084572 -0.475720654 0.334798214 -0.126125233
## EP_NOINT 0.61661332 0.58972671 -0.295302858 0.375961799 0.325399859
## EP_AGE65 -0.66361183 -0.66248150 0.939372902 -0.654215416 0.138541074
## EP_AGE17 0.59712067 0.57936954 -0.638226173 0.954467634 0.006611514
## EP_DISABL 0.08375585 0.07278448 0.187332739 -0.068795605 0.814216441
## EP_LIMENG 0.64708261 0.62373262 -0.504651099 0.492988342 -0.073997968
## EP_MOBILE -0.07058019 -0.06823345 0.053404356 -0.069919112 0.010664599
## EP_GROUPQ -0.11711812 -0.12454113 0.165910330 -0.235343454 0.034324525
## EP_BPHIGH 0.13097362 0.13053612 0.181721223 0.043825068 0.272947579
## EP_ASTHMA 0.63183706 0.62650407 -0.458382794 0.518905754 0.152228816
## EP_CANCER -0.73455797 -0.73815197 0.820069046 -0.604051891 0.097991449
## EP_MHLTH 0.83732123 0.81570491 -0.668535551 0.691473844 0.136223187
## EP_DIABETES 0.62545825 0.61256572 -0.288292716 0.488434639 0.250845085
## EPL_BPHIGH 0.17062134 0.16805200 0.138775189 0.075881806 0.272477293
## EPL_ASTHMA 0.75270202 0.76241949 -0.573966503 0.541765192 0.111922887
## EPL_CANCER -0.75683361 -0.75925826 0.834895999 -0.623898814 0.071074787
## EPL_DIABETES 0.71278346 0.71186314 -0.405820812 0.547074528 0.202413642
## EPL_MHLTH 0.89621757 0.87668241 -0.719345184 0.722444400 0.147858095
## EPL_LIMENG SPL_SVM_DOM3 RPL_SVM_DOM3 EPL_MOBILE
## E_TOTPOP 0.173162374 0.087442846 0.1210377318 -0.058135856
## M_TOTPOP 0.158109944 0.062528891 0.0955563686 -0.043297846
## E_DAYPOP 0.045422018 0.001981533 0.0142199198 -0.024719933
## SPL_EJI 0.500768878 0.382362295 0.3818456047 -0.002016489
## RPL_EJI 0.491335408 0.329428704 0.3345174145 -0.008480951
## SPL_SER 0.640503691 0.397857854 0.4121305453 0.057802084
## RPL_SER 0.614024166 0.356396027 0.3716423530 0.045622423
## EPL_OZONE -0.435571912 -0.220280871 -0.2534842737 0.049824813
## EPL_PM 0.072104341 -0.149312707 -0.1145880103 0.073574363
## EPL_DSLPM 0.578633620 0.232062481 0.2553106903 -0.058452436
## EPL_TOTCR 0.546599863 0.273882492 0.2945228229 -0.055373843
## SPL_EBM_THEME1 0.141141176 -0.017038984 -0.0216471421 0.023359316
## RPL_EBM_DOM1 0.138467818 -0.017553714 -0.0233856091 0.015466929
## EPL_NPL NA NA NA NA
## EPL_TRI 0.175387407 0.184164212 0.1752840132 -0.100201911
## EPL_TSD -0.032724026 -0.014273957 -0.0004315695 -0.021683880
## EPL_RMP 0.041655651 -0.159840115 -0.1428145087 0.095797679
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.199051389 0.040741676 0.0483970118 -0.018762775
## RPL_EBM_DOM2 0.235824333 0.051560915 0.0583106501 -0.022956425
## EPL_PARK -0.120525569 -0.030296022 -0.0454401103 -0.030218104
## EPL_HOUAGE -0.167328107 -0.154449619 -0.1623336701 0.109361782
## EPL_WLKIND -0.010438570 0.054514143 0.0422875342 0.023395206
## SPL_EBM_THEME3 -0.139493059 -0.089017173 -0.1025298570 0.093427886
## RPL_EBM_DOM3 -0.135824397 -0.086265553 -0.1032480084 0.096149178
## EPL_RAIL 0.156889123 -0.071382665 -0.0474611199 0.060222114
## EPL_ROAD 0.045187396 -0.088975138 -0.0677111582 0.006822501
## EPL_AIRPRT 0.037522144 0.058688843 0.0341289134 0.064701215
## SPL_EBM_THEME4 0.164073404 -0.059286009 -0.0446426634 0.084567739
## RPL_EBM_DOM4 0.162322810 -0.065397035 -0.0490829536 0.076730275
## EPL_IMPWTR 0.468508959 0.110824847 0.1285809721 -0.007338135
## SPL_EBM_THEME5 0.468508959 0.110824847 0.1285809721 -0.007338135
## RPL_EBM_DOM5 0.468518354 0.110772237 0.1285254022 -0.007251370
## SPL_EBM 0.194320829 -0.019853443 -0.0141497645 0.056782288
## RPL_EBM 0.221926685 -0.024081821 -0.0168509212 0.051571026
## EPL_MINRTY 0.487361893 0.186522659 0.1955278440 -0.039199048
## SPL_SVM_DOM1 0.487361893 0.186522659 0.1955278440 -0.039199048
## RPL_SVM_DOM1 0.487361893 0.186522659 0.1955278440 -0.039199048
## EPL_POV200 0.656484071 0.365641412 0.3825775885 -0.039312653
## EPL_NOHSDP 0.672470508 0.342555749 0.3615496540 -0.003813159
## EPL_UNEMP 0.271770883 0.097543127 0.0994289931 -0.033385195
## EPL_RENTER 0.580855323 0.245351897 0.2646133399 -0.040872984
## EPL_HOUBDN 0.571179405 0.189032261 0.2135280873 -0.038704892
## EPL_UNINSUR 0.382563745 -0.040508892 0.0153166353 0.013813237
## EPL_NOINT 0.362887939 0.347130490 0.3210682846 0.005202222
## SPL_SVM_DOM2 0.639615696 0.283191799 0.3037481980 -0.025412254
## RPL_SVM_DOM2 0.628828059 0.262819828 0.2816512082 -0.023832171
## EPL_AGE65 -0.494070714 0.122794166 0.0540958453 0.025112884
## EPL_AGE17 0.525076486 0.458960461 0.4874943828 -0.063741603
## EPL_DISABL 0.073096076 0.732633349 0.6757296331 -0.019266015
## EPL_LIMENG 1.000000000 0.419036174 0.4643126530 -0.153587823
## SPL_SVM_DOM3 0.419036174 1.000000000 0.9541410842 -0.093140693
## RPL_SVM_DOM3 0.464312653 0.954141084 1.0000000000 -0.123518974
## EPL_MOBILE -0.153587823 -0.093140693 -0.1235189738 1.000000000
## EPL_GROUPQ 0.098499932 0.117287730 0.1219537447 0.023366393
## SPL_SVM_DOM4 0.010293215 0.055886943 0.0451425996 0.506329422
## RPL_SVM_DOM4 0.002177128 0.056312122 0.0488819247 0.493143538
## SPL_SVM 0.645833459 0.514992344 0.5162535574 0.093243670
## RPL_SVM 0.660642423 0.482074393 0.4957837548 0.045651652
## F_BPHIGH -0.172124839 0.171815771 0.1109353000 0.010026273
## F_ASTHMA 0.330597309 0.098903002 0.1068773070 -0.013661211
## F_CANCER -0.347983256 -0.008809103 -0.0006833674 -0.070184177
## F_MHLTH 0.509992133 0.310265858 0.3294238983 -0.051265626
## F_DIABETES 0.357072591 0.174790427 0.1740489695 -0.041522203
## F_HVM 0.275523982 0.288815608 0.2756871545 -0.053042650
## RPL_HVM 0.275523982 0.288815608 0.2756871545 -0.053042650
## E_OZONE -0.489624901 -0.218065022 -0.2493054278 0.032613014
## E_PM 0.075562175 -0.147735292 -0.1129225579 0.071503971
## E_DSLPM 0.567114795 0.233185804 0.2672223804 -0.056084389
## E_TOTCR 0.539535222 0.289889749 0.3135497767 -0.061214481
## E_NPL NA NA NA NA
## E_TRI 0.210836448 0.185285162 0.1789934246 -0.112504775
## E_TSD -0.032724026 -0.014273957 -0.0004315695 -0.021683880
## E_RMP 0.105834534 -0.098660790 -0.0734741903 0.059631479
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.117480690 0.022142625 0.0355558100 0.029747537
## E_HOUAGE -0.161746848 -0.146502961 -0.1544310244 0.109873059
## E_WLKIND 0.001647109 -0.057920829 -0.0477974556 -0.018973834
## E_RAIL 0.162459932 -0.074569775 -0.0497305169 0.052081305
## E_ROAD 0.031736323 -0.101164434 -0.0760580714 -0.002509688
## E_AIRPRT 0.042387505 -0.028361478 -0.0252022895 -0.003836879
## E_IMPWTR 0.390830186 0.087214783 0.0992291658 0.001718729
## EP_MINRTY 0.474211394 0.173917982 0.1813967859 -0.029269078
## EP_POV200 0.611611713 0.398251434 0.4075569028 -0.043131435
## EP_NOHSDP 0.630593912 0.416228284 0.4135985645 -0.030065880
## EP_UNEMP 0.246581333 0.179911005 0.1817496728 -0.046898538
## EP_RENTER 0.639920566 0.260907415 0.2817772338 -0.047905474
## EP_HOUBDN 0.535687844 0.206353350 0.2418585319 -0.048412730
## EP_UNINSUR 0.384148775 -0.035611961 0.0233050422 0.002453157
## EP_NOINT 0.341412633 0.372558692 0.3332452741 -0.002906652
## EP_AGE65 -0.467399617 0.110873828 0.0615802919 -0.002757004
## EP_AGE17 0.486689483 0.423543425 0.4475350609 -0.042191453
## EP_DISABL -0.029801112 0.544619270 0.4864873628 -0.023252027
## EP_LIMENG 0.813643588 0.238731110 0.2732918495 -0.012481537
## EP_MOBILE -0.192733406 -0.073302720 -0.1009311602 0.882935982
## EP_GROUPQ -0.156626105 -0.089941117 -0.0768505590 -0.023889929
## EP_BPHIGH -0.124388422 0.280079929 0.2528779248 -0.036698905
## EP_ASTHMA 0.214571425 0.218292851 0.2173019491 0.008428629
## EP_CANCER -0.513998319 0.022681463 -0.0002464860 -0.026708583
## EP_MHLTH 0.542892799 0.298106481 0.3086577924 -0.022930296
## EP_DIABETES 0.395586067 0.437492693 0.4198578430 -0.040634871
## EPL_BPHIGH -0.089121903 0.284749840 0.2519951341 -0.044941134
## EPL_ASTHMA 0.321456499 0.164752577 0.1673244276 0.014187515
## EPL_CANCER -0.537177974 -0.004924552 -0.0213263260 -0.031605337
## EPL_DIABETES 0.473034395 0.394683480 0.4025460101 -0.072927793
## EPL_MHLTH 0.574049704 0.301850997 0.3162356302 -0.017140229
## EPL_GROUPQ SPL_SVM_DOM4 RPL_SVM_DOM4 SPL_SVM RPL_SVM
## E_TOTPOP 0.162360961 0.111784461 0.090832819 0.2313382355 0.22986219
## M_TOTPOP 0.142615154 0.101966066 0.076581011 0.2703465318 0.27975998
## E_DAYPOP 0.246840201 0.200900154 0.209366213 0.1325771132 0.12299844
## SPL_EJI 0.216106241 0.185427617 0.171879389 0.8522251757 0.85582621
## RPL_EJI 0.202954638 0.170940510 0.158663847 0.8243085314 0.84418514
## SPL_SER 0.258643456 0.251201425 0.235905170 0.9112850927 0.93167729
## RPL_SER 0.224903295 0.216176548 0.201705773 0.8713403658 0.90737031
## EPL_OZONE -0.168838887 -0.121412777 -0.125558982 -0.4440253424 -0.41846653
## EPL_PM 0.142184770 0.158415073 0.156038914 0.1602464042 0.17075892
## EPL_DSLPM 0.072120590 0.033791401 0.035190195 0.5285449209 0.51780551
## EPL_TOTCR 0.050936133 0.017014938 0.019256671 0.5372242996 0.52896873
## SPL_EBM_THEME1 -0.101501276 -0.076195834 -0.080011273 0.1396006859 0.16639147
## RPL_EBM_DOM1 -0.106331021 -0.084198928 -0.087103872 0.1218958535 0.14905392
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.034664308 -0.018814990 -0.014619463 0.1735875032 0.16095586
## EPL_TSD 0.067225816 0.047445210 0.057968757 0.0288240197 0.03405864
## EPL_RMP 0.038610325 0.079878680 0.077877025 -0.0065816569 0.01430505
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.074900368 0.055485257 0.059269112 0.1651894500 0.17131063
## RPL_EBM_DOM2 0.056349801 0.037445146 0.038982933 0.1735208656 0.18138466
## EPL_PARK 0.033298321 0.014031060 0.013152489 -0.1231185269 -0.13090884
## EPL_HOUAGE -0.219624928 -0.136274245 -0.134816490 -0.2705710984 -0.25461322
## EPL_WLKIND -0.116466648 -0.089087150 -0.090308810 0.0564091016 0.04692232
## SPL_EBM_THEME3 -0.226952811 -0.150341746 -0.149956406 -0.1814372302 -0.17500097
## RPL_EBM_DOM3 -0.219195284 -0.142327270 -0.142522814 -0.1685382358 -0.16425511
## EPL_RAIL 0.111174543 0.125174888 0.123046864 0.2732236815 0.29253108
## EPL_ROAD -0.023250846 -0.016738690 -0.005591004 -0.0005663096 0.00664797
## EPL_AIRPRT 0.029688209 0.057064383 0.055853540 0.0814465772 0.06964534
## SPL_EBM_THEME4 0.099773360 0.127176719 0.128439312 0.2678839756 0.28044726
## RPL_EBM_DOM4 0.096632653 0.120657249 0.120282191 0.2673214048 0.28351402
## EPL_IMPWTR -0.043178296 -0.040812158 -0.050632167 0.5136867319 0.52801458
## SPL_EBM_THEME5 -0.043178296 -0.040812158 -0.050632167 0.5136867319 0.52801458
## RPL_EBM_DOM5 -0.043169518 -0.040762403 -0.050596206 0.5136851360 0.52802102
## SPL_EBM -0.026278443 0.004938935 0.007071500 0.1884914738 0.20351485
## RPL_EBM -0.025788765 0.002827738 0.004473238 0.2156209089 0.23467659
## EPL_MINRTY -0.019050662 -0.035490200 -0.050719570 0.6457454226 0.67068673
## SPL_SVM_DOM1 -0.019050662 -0.035490200 -0.050719570 0.6457454226 0.67068673
## RPL_SVM_DOM1 -0.019050662 -0.035490200 -0.050719570 0.6457454226 0.67068673
## EPL_POV200 0.119125128 0.083641639 0.070797323 0.8868511254 0.89957996
## EPL_NOHSDP 0.089823502 0.075625706 0.069968569 0.8167139286 0.84022146
## EPL_UNEMP 0.144151770 0.108110788 0.106232074 0.5703930947 0.55603180
## EPL_RENTER 0.071691823 0.041968233 0.028579906 0.7370045594 0.76150216
## EPL_HOUBDN 0.009981495 -0.010207523 -0.023098823 0.7603355876 0.80308158
## EPL_UNINSUR 0.066895303 0.064417898 0.039891806 0.5336046030 0.53678075
## EPL_NOINT 0.110314945 0.097684171 0.072609009 0.6730740297 0.65729999
## SPL_SVM_DOM2 0.120445502 0.091538576 0.073254545 0.9241894307 0.93545071
## RPL_SVM_DOM2 0.091194618 0.067075671 0.048544257 0.9071312710 0.93319538
## EPL_AGE65 -0.023383819 -0.007961078 0.009596655 -0.5491927698 -0.56227636
## EPL_AGE17 0.065420147 0.025440306 0.016733101 0.6836211649 0.67630123
## EPL_DISABL 0.089190089 0.067566561 0.062364911 0.3111944209 0.27143543
## EPL_LIMENG 0.098499932 0.010293215 0.002177128 0.6458334592 0.66064242
## SPL_SVM_DOM3 0.117287730 0.055886943 0.056312122 0.5149923440 0.48207439
## RPL_SVM_DOM3 0.121953745 0.045142600 0.048881925 0.5162535574 0.49578375
## EPL_MOBILE 0.023366393 0.506329422 0.493143538 0.0932436696 0.04565165
## EPL_GROUPQ 1.000000000 0.873935786 0.871579829 0.3648761060 0.31787902
## SPL_SVM_DOM4 0.873935786 1.000000000 0.991557173 0.3600659052 0.29638935
## RPL_SVM_DOM4 0.871579829 0.991557173 1.000000000 0.3425320674 0.27753660
## SPL_SVM 0.364876106 0.360065905 0.342532067 1.0000000000 0.98427600
## RPL_SVM 0.317879020 0.296389355 0.277536600 0.9842759983 1.00000000
## F_BPHIGH -0.002036662 0.003117740 0.003257837 0.1301662416 0.11189182
## F_ASTHMA -0.054759304 -0.053875770 -0.067587600 0.6015296937 0.63087621
## F_CANCER 0.143528580 0.089682526 0.110511508 -0.4756931699 -0.49778969
## F_MHLTH 0.192692473 0.141287814 0.125772260 0.7185671111 0.68802731
## F_DIABETES 0.103064112 0.068713572 0.057400417 0.6046657012 0.62132706
## F_HVM 0.134181679 0.089953884 0.080751516 0.6226326579 0.61103633
## RPL_HVM 0.134181679 0.089953884 0.080751516 0.6226326579 0.61103633
## E_OZONE -0.180658572 -0.139976081 -0.142443302 -0.4992959250 -0.47470195
## E_PM 0.145162361 0.159976899 0.157629411 0.1690470087 0.17926207
## E_DSLPM 0.076437598 0.038666431 0.037000527 0.5164070563 0.50469466
## E_TOTCR 0.048195259 0.011811159 0.013366878 0.5471384135 0.53651352
## E_NPL NA NA NA NA NA
## E_TRI 0.033943678 -0.025417922 -0.022674779 0.2117659998 0.20081136
## E_TSD 0.067225816 0.047445210 0.057968757 0.0288240197 0.03405864
## E_RMP -0.024634994 0.007741737 0.001184790 0.0082529000 0.03027985
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK -0.028793340 -0.010373951 -0.008384719 0.1189766900 0.12592901
## E_HOUAGE -0.214154297 -0.131306842 -0.129228614 -0.2585198481 -0.24281058
## E_WLKIND 0.113198957 0.088418077 0.089605764 -0.0603188086 -0.04974432
## E_RAIL 0.119223428 0.128159809 0.126936644 0.2738206614 0.29404171
## E_ROAD -0.023696775 -0.021660406 -0.011104786 -0.0191510100 -0.01108701
## E_AIRPRT 0.065136717 0.054319955 0.063168157 0.0571996120 0.05152026
## E_IMPWTR -0.059421448 -0.050419893 -0.059029153 0.4635354886 0.47927825
## EP_MINRTY -0.017224233 -0.029087073 -0.045112345 0.6462673399 0.67149367
## EP_POV200 0.139053511 0.098974784 0.091404717 0.8492180952 0.84068427
## EP_NOHSDP 0.120505493 0.089327851 0.085422962 0.7943782701 0.77961141
## EP_UNEMP 0.185275699 0.137013450 0.142291351 0.5304411830 0.50355551
## EP_RENTER 0.101072539 0.063892308 0.053082257 0.7789337725 0.78816128
## EP_HOUBDN 0.101979641 0.064428138 0.060415822 0.7063044413 0.72880692
## EP_UNINSUR 0.084131027 0.073762037 0.050702065 0.5078488042 0.50363605
## EP_NOINT 0.091745748 0.077724509 0.059762992 0.6298857921 0.60170090
## EP_AGE65 0.044302306 0.036873706 0.060815807 -0.5186895805 -0.53389089
## EP_AGE17 0.016549788 -0.006236950 -0.016571443 0.6135718905 0.60138289
## EP_DISABL 0.109549864 0.083190511 0.089104000 0.2302389565 0.20086291
## EP_LIMENG 0.103568588 0.083267542 0.069374070 0.6197689716 0.62020693
## EP_MOBILE 0.013200757 0.440647294 0.424766824 0.0447907507 0.01018086
## EP_GROUPQ 0.413754449 0.345279847 0.390315100 -0.0402050926 -0.05226951
## EP_BPHIGH 0.017130351 -0.003065835 0.001416840 0.2031237787 0.19220724
## EP_ASTHMA 0.033586361 0.033068559 0.024937643 0.6069906437 0.59688353
## EP_CANCER -0.011265996 -0.022702796 -0.004560913 -0.6228586605 -0.64110779
## EP_MHLTH 0.109037036 0.082904575 0.073070583 0.7968560882 0.78275933
## EP_DIABETES 0.040339341 0.015040109 0.008525962 0.6535362039 0.63997735
## EPL_BPHIGH 0.040202084 0.012828122 0.015261829 0.2429409034 0.22888162
## EPL_ASTHMA 0.012076571 0.017314559 0.002786967 0.6906777593 0.70219373
## EPL_CANCER -0.008909423 -0.023050749 -0.004425679 -0.6515676033 -0.67045311
## EPL_DIABETES 0.066965253 0.022306989 0.011230891 0.7252573934 0.73525076
## EPL_MHLTH 0.131724702 0.105289385 0.092614984 0.8524028426 0.84458322
## F_BPHIGH F_ASTHMA F_CANCER F_MHLTH F_DIABETES
## E_TOTPOP 0.029018882 0.18988395 -0.0804588594 0.170660883 0.19450796
## M_TOTPOP 0.056477775 0.24574131 -0.1481661483 0.186228688 0.25675371
## E_DAYPOP 0.003944683 0.05531251 0.0245487686 0.037223606 0.05015995
## SPL_EJI 0.448499138 0.74142005 -0.3753282495 0.749225719 0.80803710
## RPL_EJI 0.404320683 0.76807981 -0.3600929861 0.681200328 0.82212870
## SPL_SER 0.090628517 0.60828882 -0.4589043414 0.626182031 0.60008497
## RPL_SER 0.096252164 0.61082861 -0.4511022884 0.577127342 0.59406488
## EPL_OZONE -0.050060681 -0.20563859 0.1090961159 -0.500515703 -0.27808107
## EPL_PM 0.074811862 0.12757422 0.0013061460 0.138448710 0.15784613
## EPL_DSLPM 0.001284592 0.36947440 -0.3222534364 0.514378330 0.39490280
## EPL_TOTCR 0.029680364 0.38710368 -0.3376934813 0.484425896 0.38388035
## SPL_EBM_THEME1 -0.009427114 0.25350124 -0.2725058963 0.001398471 0.17265501
## RPL_EBM_DOM1 -0.019198914 0.24205932 -0.2622124590 -0.018807220 0.16004620
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.086844456 0.08335216 -0.0323846057 0.204914006 0.16968061
## EPL_TSD -0.046449782 0.02329743 -0.0180662871 -0.060393844 -0.11349779
## EPL_RMP -0.218926516 -0.05593676 -0.0230752279 -0.091089185 -0.13762300
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 -0.106784538 0.03627596 -0.0529616014 0.112145323 0.03196673
## RPL_EBM_DOM2 -0.101641740 0.04357442 -0.0614874977 0.130527375 0.05697449
## EPL_PARK -0.064731235 -0.18181356 0.1281443043 -0.084163326 -0.15816764
## EPL_HOUAGE -0.042366227 -0.14059838 0.1775164148 -0.299305057 -0.13551690
## EPL_WLKIND 0.143060825 0.12450546 -0.0276231710 0.072452890 0.09805454
## SPL_EBM_THEME3 0.041498900 -0.04997995 0.1270417345 -0.192052122 -0.05901171
## RPL_EBM_DOM3 0.045201643 -0.03752566 0.1226242676 -0.180534782 -0.04262736
## EPL_RAIL 0.095166325 0.28614201 -0.0506351820 0.181023468 0.31427872
## EPL_ROAD 0.041898504 0.07493349 -0.0962142336 0.025822871 0.05639664
## EPL_AIRPRT -0.016904605 0.04045631 -0.0313723573 0.025056477 0.04650450
## SPL_EBM_THEME4 0.084519883 0.28288594 -0.0891702070 0.171654168 0.30327995
## RPL_EBM_DOM4 0.085856035 0.28881287 -0.0796549429 0.169155049 0.31000416
## EPL_IMPWTR -0.016153863 0.51114032 -0.4795891322 0.398603538 0.43724716
## SPL_EBM_THEME5 -0.016153863 0.51114032 -0.4795891322 0.398603538 0.43724716
## RPL_EBM_DOM5 -0.016154026 0.51115849 -0.4796076151 0.398597201 0.43726100
## SPL_EBM -0.035091843 0.16593166 -0.0790445246 0.091064999 0.15177484
## RPL_EBM -0.010181763 0.20294748 -0.1037751820 0.121762424 0.20256047
## EPL_MINRTY 0.284409899 0.67739274 -0.6706685058 0.500000056 0.72959896
## SPL_SVM_DOM1 0.284409899 0.67739274 -0.6706685058 0.500000056 0.72959896
## RPL_SVM_DOM1 0.284409899 0.67739274 -0.6706685058 0.500000056 0.72959896
## EPL_POV200 0.090659309 0.67821972 -0.5637100412 0.745051759 0.63077328
## EPL_NOHSDP 0.127034051 0.63318537 -0.5650898559 0.648372559 0.62659447
## EPL_UNEMP 0.065320622 0.33790543 -0.3114517529 0.409711370 0.29387471
## EPL_RENTER -0.013258667 0.55484687 -0.4045652708 0.601627222 0.49154333
## EPL_HOUBDN 0.031189845 0.67352849 -0.6026102403 0.532348551 0.56697914
## EPL_UNINSUR -0.146611495 0.44061204 -0.3128274849 0.349857124 0.30665154
## EPL_NOINT 0.261688159 0.45696134 -0.3751066905 0.602688703 0.47075417
## SPL_SVM_DOM2 0.076681201 0.69506215 -0.5755973767 0.723658583 0.62199804
## RPL_SVM_DOM2 0.076190808 0.71820985 -0.5980586690 0.683140651 0.62461077
## EPL_AGE65 0.140232064 -0.53064894 0.6115440030 -0.579400336 -0.42012938
## EPL_AGE17 -0.016753641 0.45446408 -0.4294965172 0.613893156 0.44667370
## EPL_DISABL 0.244571310 0.05166226 -0.0195034219 0.165598424 0.03875092
## EPL_LIMENG -0.172124839 0.33059731 -0.3479832558 0.509992133 0.35707259
## SPL_SVM_DOM3 0.171815771 0.09890300 -0.0088091029 0.310265858 0.17479043
## RPL_SVM_DOM3 0.110935300 0.10687731 -0.0006833674 0.329423898 0.17404897
## EPL_MOBILE 0.010026273 -0.01366121 -0.0701841771 -0.051265626 -0.04152220
## EPL_GROUPQ -0.002036662 -0.05475930 0.1435285801 0.192692473 0.10306411
## SPL_SVM_DOM4 0.003117740 -0.05387577 0.0896825263 0.141287814 0.06871357
## RPL_SVM_DOM4 0.003257837 -0.06758760 0.1105115080 0.125772260 0.05740042
## SPL_SVM 0.130166242 0.60152969 -0.4756931699 0.718567111 0.60466570
## RPL_SVM 0.111891822 0.63087621 -0.4977896869 0.688027309 0.62132706
## F_BPHIGH 1.000000000 0.23596788 -0.0474842176 0.139226569 0.37796185
## F_ASTHMA 0.235967883 1.00000000 -0.5469781012 0.462910050 0.71941444
## F_CANCER -0.047484218 -0.54697810 1.0000000000 -0.358969442 -0.41405083
## F_MHLTH 0.139226569 0.46291005 -0.3589694422 1.000000000 0.50114507
## F_DIABETES 0.377961850 0.71941444 -0.4140508270 0.501145073 1.00000000
## F_HVM 0.662204675 0.70037554 -0.2247020698 0.697867431 0.81736896
## RPL_HVM 0.662204675 0.70037554 -0.2247020698 0.697867431 0.81736896
## E_OZONE -0.002906493 -0.22579662 0.1422250005 -0.537722405 -0.29533328
## E_PM 0.080741770 0.13728522 -0.0020191253 0.146924570 0.16760967
## E_DSLPM 0.002814397 0.34082320 -0.2682278822 0.536770631 0.37569665
## E_TOTCR 0.053878146 0.38314555 -0.3150499462 0.515412330 0.38480008
## E_NPL NA NA NA NA NA
## E_TRI 0.078037091 0.10805786 -0.0688421058 0.218091373 0.18333216
## E_TSD -0.046449782 0.02329743 -0.0180662871 -0.060393844 -0.11349779
## E_RMP -0.180743709 -0.03273497 -0.0269002854 -0.076344335 -0.09498459
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.063723217 0.17898230 -0.1357227482 0.082852704 0.15570459
## E_HOUAGE -0.036507017 -0.13327547 0.1718899258 -0.290704279 -0.12806780
## E_WLKIND -0.146528000 -0.12835914 0.0224062502 -0.077894482 -0.09939590
## E_RAIL 0.098341344 0.28219369 -0.0385192974 0.182207596 0.31824988
## E_ROAD 0.039831150 0.05558265 -0.0765094391 0.017231686 0.03716762
## E_AIRPRT -0.040987165 0.02729600 -0.0211670245 0.052318568 0.03137672
## E_IMPWTR 0.009547207 0.50376797 -0.4881215069 0.348904353 0.41182886
## EP_MINRTY 0.283721500 0.69346497 -0.6706951326 0.495137885 0.74000359
## EP_POV200 0.137059784 0.60603807 -0.4744254210 0.758301875 0.58940126
## EP_NOHSDP 0.153096465 0.53787372 -0.4513538484 0.731097642 0.55926620
## EP_UNEMP 0.102892018 0.28121665 -0.2643464037 0.427835848 0.28770138
## EP_RENTER 0.009928528 0.56673481 -0.4305148028 0.699318372 0.52449720
## EP_HOUBDN -0.013136033 0.55566968 -0.4717046797 0.561064145 0.51062177
## EP_UNINSUR -0.180993953 0.38922016 -0.2803186772 0.355622993 0.28391717
## EP_NOINT 0.304196495 0.41044224 -0.3289783239 0.592429011 0.43890459
## EP_AGE65 0.156648963 -0.51873860 0.6575043551 -0.523198605 -0.36006055
## EP_AGE17 0.010984184 0.41473151 -0.4099132016 0.570392449 0.41929935
## EP_DISABL 0.225430702 0.04101993 0.0561308363 0.094888351 0.02867425
## EP_LIMENG -0.215586770 0.36628933 -0.3306078182 0.571819840 0.39088728
## EP_MOBILE 0.010602764 -0.04736960 -0.0664175312 -0.076963720 -0.08591939
## EP_GROUPQ 0.033513139 -0.13668929 0.2503823200 -0.058758638 -0.09778050
## EP_BPHIGH 0.789102666 0.33335202 0.0544021921 0.180349173 0.50578561
## EP_ASTHMA 0.528435094 0.65191428 -0.4533876752 0.662576571 0.63286433
## EP_CANCER 0.159279150 -0.58625767 0.7464006024 -0.559027121 -0.43521228
## EP_MHLTH 0.197894640 0.63889359 -0.5282930775 0.823586488 0.58387114
## EP_DIABETES 0.535322627 0.56800143 -0.3257184745 0.617159626 0.67622023
## EPL_BPHIGH 0.819299560 0.37651084 0.0126386614 0.238083707 0.54493521
## EPL_ASTHMA 0.399457977 0.84965612 -0.5771807060 0.645810277 0.75447764
## EPL_CANCER 0.093319992 -0.60879308 0.8038312131 -0.576789846 -0.51037864
## EPL_DIABETES 0.458065260 0.71412089 -0.4051377543 0.599972020 0.84772245
## EPL_MHLTH 0.176590441 0.69757803 -0.5655579721 0.861422527 0.64290705
## F_HVM RPL_HVM E_OZONE E_PM E_DSLPM
## E_TOTPOP 0.18649078 0.18649078 -0.0644917730 0.076745301 0.126101355
## M_TOTPOP 0.22526278 0.22526278 -0.0248459418 0.077646920 0.065142298
## E_DAYPOP 0.05704113 0.05704113 -0.0410353118 -0.017960560 0.024253193
## SPL_EJI 0.90399403 0.90399403 -0.4616506858 0.232085644 0.500719267
## RPL_EJI 0.87344680 0.87344680 -0.4324730571 0.273295934 0.475082311
## SPL_SER 0.57186182 0.57186182 -0.4677722449 0.221144588 0.508217706
## RPL_SER 0.55422842 0.55422842 -0.4286596930 0.245489244 0.485092499
## EPL_OZONE -0.35995919 -0.35995919 0.9499947598 -0.411554933 -0.744807330
## EPL_PM 0.18137972 0.18137972 -0.4914561307 0.999321251 0.152086098
## EPL_DSLPM 0.38068378 0.38068378 -0.6336388541 0.130332644 0.925446841
## EPL_TOTCR 0.37771492 0.37771492 -0.5692981861 -0.022426672 0.803651881
## SPL_EBM_THEME1 0.06286709 0.06286709 0.3478314929 -0.159801207 0.107050248
## RPL_EBM_DOM1 0.04516021 0.04516021 0.3775361754 -0.181080242 0.088296157
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.19651104 0.19651104 -0.1000988250 -0.414482911 0.394468255
## EPL_TSD -0.08015841 -0.08015841 -0.1045026123 0.029640999 0.023405063
## EPL_RMP -0.19853614 -0.19853614 -0.0650635623 0.349192690 -0.284350478
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.01112241 0.01112241 -0.1650730287 -0.100891064 0.143356168
## RPL_EBM_DOM2 0.02944086 0.02944086 -0.1604243399 -0.102784945 0.163830053
## EPL_PARK -0.13837554 -0.13837554 0.1505597729 -0.252658442 -0.172596367
## EPL_HOUAGE -0.18738579 -0.18738579 0.2145204370 0.178638640 -0.164506906
## EPL_WLKIND 0.15392101 0.15392101 0.0024282690 -0.033048118 0.002488146
## SPL_EBM_THEME3 -0.06671363 -0.06671363 0.1726570403 0.101475640 -0.133569453
## RPL_EBM_DOM3 -0.05216959 -0.05216959 0.1565821704 0.092234813 -0.125954956
## EPL_RAIL 0.29513646 0.29513646 -0.3317833860 0.567893150 0.210622405
## EPL_ROAD 0.04583056 0.04583056 -0.0726290956 0.214464170 0.097282643
## EPL_AIRPRT 0.02343544 0.02343544 -0.0060693668 -0.116528100 -0.020252393
## SPL_EBM_THEME4 0.27241409 0.27241409 -0.3030401273 0.484973211 0.197081966
## RPL_EBM_DOM4 0.27834595 0.27834595 -0.3130430632 0.524561962 0.200901657
## EPL_IMPWTR 0.34222998 0.34222998 -0.3679456932 0.077584569 0.548460403
## SPL_EBM_THEME5 0.34222998 0.34222998 -0.3679456932 0.077584569 0.548460403
## RPL_EBM_DOM5 0.34223274 0.34223274 -0.3680631062 0.077893195 0.548565460
## SPL_EBM 0.10495174 0.10495174 -0.1509021012 0.123668093 0.171530278
## RPL_EBM 0.15028107 0.15028107 -0.1796422605 0.186908698 0.220133188
## EPL_MINRTY 0.61057621 0.61057621 -0.2871116913 0.115456224 0.434772054
## SPL_SVM_DOM1 0.61057621 0.61057621 -0.2871116913 0.115456224 0.434772054
## RPL_SVM_DOM1 0.61057621 0.61057621 -0.2871116913 0.115456224 0.434772054
## EPL_POV200 0.62723811 0.62723811 -0.5255597960 0.153609461 0.561639803
## EPL_NOHSDP 0.58619769 0.58619769 -0.3646548898 0.088276924 0.498760090
## EPL_UNEMP 0.32270788 0.32270788 -0.2714288225 0.173237868 0.256428370
## EPL_RENTER 0.47932862 0.47932862 -0.5081459763 0.219980383 0.476837063
## EPL_HOUBDN 0.48017817 0.48017817 -0.3422715060 0.131676526 0.448615247
## EPL_UNINSUR 0.24404728 0.24404728 -0.2950830941 0.216868945 0.285545808
## EPL_NOINT 0.56533502 0.56533502 -0.3341585099 0.078653710 0.349396779
## SPL_SVM_DOM2 0.61158303 0.61158303 -0.4936441570 0.201417388 0.530768938
## RPL_SVM_DOM2 0.59654736 0.59654736 -0.4546754808 0.195180130 0.508120923
## EPL_AGE65 -0.33384142 -0.33384142 0.4327849014 -0.182323388 -0.457843341
## EPL_AGE17 0.43133245 0.43133245 -0.4173373175 0.094024997 0.425594349
## EPL_DISABL 0.19577768 0.19577768 -0.0894577150 -0.193527592 0.090641095
## EPL_LIMENG 0.27552398 0.27552398 -0.4896249014 0.075562175 0.567114795
## SPL_SVM_DOM3 0.28881561 0.28881561 -0.2180650218 -0.147735292 0.233185804
## RPL_SVM_DOM3 0.27568715 0.27568715 -0.2493054278 -0.112922558 0.267222380
## EPL_MOBILE -0.05304265 -0.05304265 0.0326130138 0.071503971 -0.056084389
## EPL_GROUPQ 0.13418168 0.13418168 -0.1806585717 0.145162361 0.076437598
## SPL_SVM_DOM4 0.08995388 0.08995388 -0.1399760809 0.159976899 0.038666431
## RPL_SVM_DOM4 0.08075152 0.08075152 -0.1424433020 0.157629411 0.037000527
## SPL_SVM 0.62263266 0.62263266 -0.4992959250 0.169047009 0.516407056
## RPL_SVM 0.61103633 0.61103633 -0.4747019503 0.179262074 0.504694659
## F_BPHIGH 0.66220467 0.66220467 -0.0029064926 0.080741770 0.002814397
## F_ASTHMA 0.70037554 0.70037554 -0.2257966239 0.137285218 0.340823195
## F_CANCER -0.22470207 -0.22470207 0.1422250005 -0.002019125 -0.268227882
## F_MHLTH 0.69786743 0.69786743 -0.5377224053 0.146924570 0.536770631
## F_DIABETES 0.81736896 0.81736896 -0.2953332806 0.167609675 0.375696651
## F_HVM 1.00000000 1.00000000 -0.3595318530 0.192804624 0.389219656
## RPL_HVM 1.00000000 1.00000000 -0.3595318530 0.192804624 0.389219656
## E_OZONE -0.35953185 -0.35953185 1.0000000000 -0.496695889 -0.686401350
## E_PM 0.19280462 0.19280462 -0.4966958895 1.000000000 0.162276051
## E_DSLPM 0.38921966 0.38921966 -0.6864013497 0.162276051 1.000000000
## E_TOTCR 0.40568523 0.40568523 -0.6345181035 -0.021765303 0.853175495
## E_NPL NA NA NA NA NA
## E_TRI 0.20130629 0.20130629 -0.1219505351 -0.407703733 0.393272366
## E_TSD -0.08015841 -0.08015841 -0.1045026123 0.029640999 0.023405063
## E_RMP -0.15606515 -0.15606515 -0.0483476107 0.344089955 -0.266730054
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.13381909 0.13381909 -0.1501479097 0.247116334 0.172488307
## E_HOUAGE -0.17801189 -0.17801189 0.2138704443 0.178208415 -0.162748579
## E_WLKIND -0.16059301 -0.16059301 0.0017513620 0.031096357 -0.004189604
## E_RAIL 0.30012475 0.30012475 -0.3417260759 0.582616129 0.213732633
## E_ROAD 0.03399566 0.03399566 -0.0594447933 0.208791649 0.083657771
## E_AIRPRT 0.01840327 0.01840327 -0.0272928960 -0.056431360 -0.002134779
## E_IMPWTR 0.31913799 0.31913799 -0.2645983146 0.068963693 0.445374390
## EP_MINRTY 0.61658118 0.61658118 -0.2909451534 0.135365945 0.429323448
## EP_POV200 0.63888683 0.63888683 -0.5168509416 0.124334352 0.553668597
## EP_NOHSDP 0.60913202 0.60913202 -0.4765274075 0.111712897 0.538206346
## EP_UNEMP 0.33858131 0.33858131 -0.2641319733 0.132969447 0.245409162
## EP_RENTER 0.53833203 0.53833203 -0.6003978032 0.273798669 0.577471189
## EP_HOUBDN 0.45202269 0.45202269 -0.3937164338 0.203297393 0.463448943
## EP_UNINSUR 0.21707961 0.21707961 -0.3034163179 0.189278988 0.286165871
## EP_NOINT 0.56558132 0.56558132 -0.3200839719 0.056686675 0.335302884
## EP_AGE65 -0.26809948 -0.26809948 0.3363955385 -0.117254222 -0.416027133
## EP_AGE17 0.40827300 0.40827300 -0.3590823987 0.073556787 0.392515540
## EP_DISABL 0.17031701 0.17031701 -0.0275696617 -0.181182589 0.051182846
## EP_LIMENG 0.30993985 0.30993985 -0.5572311130 0.261221989 0.625276414
## EP_MOBILE -0.08774106 -0.08774106 0.0535782824 0.068243898 -0.095378530
## EP_GROUPQ -0.02211772 -0.02211772 0.0006549523 0.013814858 -0.070178124
## EP_BPHIGH 0.68921327 0.68921327 -0.0109413090 0.066549469 0.067099159
## EP_ASTHMA 0.79566225 0.79566225 -0.2556639045 0.169701192 0.334944469
## EP_CANCER -0.30538418 -0.30538418 0.3684225647 -0.136015369 -0.460212575
## EP_MHLTH 0.68648544 0.68648544 -0.4582178912 0.119058758 0.536550469
## EP_DIABETES 0.80033434 0.80033434 -0.3293617652 0.045738146 0.431828184
## EPL_BPHIGH 0.74188096 0.74188096 -0.0388586064 0.071466719 0.094373289
## EPL_ASTHMA 0.80427704 0.80427704 -0.2840245921 0.174367463 0.399415648
## EPL_CANCER -0.35791894 -0.35791894 0.4161707737 -0.165418689 -0.463042650
## EPL_DIABETES 0.84243681 0.84243681 -0.3579335950 0.119239322 0.462744556
## EPL_MHLTH 0.72171457 0.72171457 -0.5134099758 0.160222484 0.562542702
## E_TOTCR E_NPL E_TRI E_TSD E_RMP
## E_TOTPOP 0.093322977 NA -0.029465353 -0.0274357505 0.084025890
## M_TOTPOP 0.052597208 NA -0.058235484 -0.0302984012 0.107208668
## E_DAYPOP 0.102668101 NA 0.049779838 0.1657402457 0.152795958
## SPL_EJI 0.548922049 NA 0.299553805 -0.0149740580 -0.024655354
## RPL_EJI 0.520393571 NA 0.280634702 -0.0051302064 -0.005354821
## SPL_SER 0.581562486 NA 0.340714130 0.0644665565 0.134145270
## RPL_SER 0.557591646 NA 0.329454901 0.0479452470 0.124502377
## EPL_OZONE -0.686464728 NA -0.202485323 -0.1566698098 0.056284089
## EPL_PM -0.034041383 NA -0.427425385 0.0283023798 0.359569488
## EPL_DSLPM 0.881819997 NA 0.427061268 0.0317671760 -0.233639863
## EPL_TOTCR 0.967901656 NA 0.524169821 0.0783880810 -0.195483568
## SPL_EBM_THEME1 0.262457904 NA 0.200533258 -0.1123100959 -0.046674352
## RPL_EBM_DOM1 0.236445119 NA 0.196014054 -0.1134391549 -0.057373130
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.528749343 NA 0.963097211 0.0429512662 -0.431159469
## EPL_TSD 0.119052921 NA 0.047529497 1.0000000000 0.034149271
## EPL_RMP -0.230738860 NA -0.386900033 0.1202062973 0.896123297
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.330446706 NA 0.606864672 0.2785097475 0.343122863
## RPL_EBM_DOM2 0.337265448 NA 0.629408560 0.1394121791 0.345204762
## EPL_PARK -0.290855426 NA -0.103912935 -0.0042357890 -0.027119845
## EPL_HOUAGE -0.282768918 NA -0.266071222 -0.1222079044 0.168090693
## EPL_WLKIND 0.008841115 NA -0.074855580 0.0787410995 0.028520434
## SPL_EBM_THEME3 -0.226759788 NA -0.247959001 -0.0499299621 0.140762129
## RPL_EBM_DOM3 -0.214063718 NA -0.238715020 -0.0606446221 0.140731038
## EPL_RAIL 0.223581989 NA 0.168872651 0.0121470949 0.073597238
## EPL_ROAD 0.126203881 NA -0.004456369 -0.0051296945 -0.038257816
## EPL_AIRPRT 0.076848703 NA 0.081857551 -0.0052781575 0.181784145
## SPL_EBM_THEME4 0.265615331 NA 0.179911116 0.0058172590 0.139242204
## RPL_EBM_DOM4 0.253351213 NA 0.174926106 0.0060755477 0.112633307
## EPL_IMPWTR 0.597540232 NA 0.296043510 0.0300239152 -0.045751775
## SPL_EBM_THEME5 0.597540232 NA 0.296043510 0.0300239152 -0.045751775
## RPL_EBM_DOM5 0.597522518 NA 0.295915035 0.0299704952 -0.045715330
## SPL_EBM 0.307451347 NA 0.440430505 0.1793230472 0.354122288
## RPL_EBM 0.344531263 NA 0.458185312 0.0955839242 0.290561894
## EPL_MINRTY 0.458027620 NA 0.229017568 -0.0035761585 -0.062782330
## SPL_SVM_DOM1 0.458027620 NA 0.229017568 -0.0035761585 -0.062782330
## RPL_SVM_DOM1 0.458027620 NA 0.229017568 -0.0035761585 -0.062782330
## EPL_POV200 0.614612108 NA 0.215925520 0.0231118450 0.064147089
## EPL_NOHSDP 0.538218976 NA 0.226367937 -0.0137064998 0.019654147
## EPL_UNEMP 0.249329728 NA 0.026682875 0.0308180322 0.027369736
## EPL_RENTER 0.492932727 NA 0.149103115 0.0292949026 0.139089134
## EPL_HOUBDN 0.470469851 NA 0.170265121 0.0143047804 0.070540769
## EPL_UNINSUR 0.280238641 NA 0.085741158 0.0776121643 0.084225609
## EPL_NOINT 0.380678592 NA 0.199809079 -0.0375231166 -0.125790549
## SPL_SVM_DOM2 0.558318760 NA 0.195561539 0.0258450985 0.049645329
## RPL_SVM_DOM2 0.538890200 NA 0.188856033 0.0285580977 0.063927013
## EPL_AGE65 -0.452012996 NA -0.111922968 -0.0685996975 -0.046459241
## EPL_AGE17 0.454572888 NA 0.162220280 0.0481932640 0.002824652
## EPL_DISABL 0.160049943 NA 0.125937230 0.0180854079 -0.178495616
## EPL_LIMENG 0.539535222 NA 0.210836448 -0.0327240263 0.105834534
## SPL_SVM_DOM3 0.289889749 NA 0.185285162 -0.0142739571 -0.098660790
## RPL_SVM_DOM3 0.313549777 NA 0.178993425 -0.0004315695 -0.073474190
## EPL_MOBILE -0.061214481 NA -0.112504775 -0.0216838799 0.059631479
## EPL_GROUPQ 0.048195259 NA 0.033943678 0.0672258159 -0.024634994
## SPL_SVM_DOM4 0.011811159 NA -0.025417922 0.0474452102 0.007741737
## RPL_SVM_DOM4 0.013366878 NA -0.022674779 0.0579687572 0.001184790
## SPL_SVM 0.547138413 NA 0.211766000 0.0288240197 0.008252900
## RPL_SVM 0.536513519 NA 0.200811365 0.0340586354 0.030279853
## F_BPHIGH 0.053878146 NA 0.078037091 -0.0464497820 -0.180743709
## F_ASTHMA 0.383145550 NA 0.108057860 0.0232974312 -0.032734970
## F_CANCER -0.315049946 NA -0.068842106 -0.0180662871 -0.026900285
## F_MHLTH 0.515412330 NA 0.218091373 -0.0603938442 -0.076344335
## F_DIABETES 0.384800078 NA 0.183332156 -0.1134977905 -0.094984585
## F_HVM 0.405685230 NA 0.201306291 -0.0801584128 -0.156065151
## RPL_HVM 0.405685230 NA 0.201306291 -0.0801584128 -0.156065151
## E_OZONE -0.634518104 NA -0.121950535 -0.1045026123 -0.048347611
## E_PM -0.021765303 NA -0.407703733 0.0296409991 0.344089955
## E_DSLPM 0.853175495 NA 0.393272366 0.0234050628 -0.266730054
## E_TOTCR 1.000000000 NA 0.543919611 0.1190529215 -0.225212479
## E_NPL NA 1 NA NA NA
## E_TRI 0.543919611 NA 1.000000000 0.0475294973 -0.383583853
## E_TSD 0.119052921 NA 0.047529497 1.0000000000 0.034149271
## E_RMP -0.225212479 NA -0.383583853 0.0341492711 1.000000000
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.293170497 NA 0.102294766 0.0041698278 0.026697525
## E_HOUAGE -0.281333327 NA -0.264221452 -0.1235347631 0.163771047
## E_WLKIND -0.013131607 NA 0.070752809 -0.0815413585 -0.026913008
## E_RAIL 0.206906554 NA 0.151778824 0.0127833370 0.078709372
## E_ROAD 0.092646453 NA -0.015555368 0.0056336013 -0.052206246
## E_AIRPRT 0.055497997 NA 0.054573291 -0.0035611889 0.180050200
## E_IMPWTR 0.528682545 NA 0.265367087 0.0223267351 -0.039809431
## EP_MINRTY 0.456302190 NA 0.218911982 0.0017535280 -0.041209450
## EP_POV200 0.611149172 NA 0.230228651 0.0096792609 0.025828865
## EP_NOHSDP 0.564367687 NA 0.238959936 -0.0379191476 -0.033389171
## EP_UNEMP 0.272112537 NA 0.020956590 0.0082596533 -0.027625828
## EP_RENTER 0.575049960 NA 0.148549515 0.0285424398 0.152099146
## EP_HOUBDN 0.466289861 NA 0.094195894 -0.0078545072 0.062734056
## EP_UNINSUR 0.287414223 NA 0.102280627 0.0930861881 0.053447852
## EP_NOINT 0.375688335 NA 0.222311956 -0.0400449515 -0.140078502
## EP_AGE65 -0.406619884 NA -0.118070996 -0.0877480636 -0.053262827
## EP_AGE17 0.399903389 NA 0.146574863 0.0375029460 -0.011965409
## EP_DISABL 0.150842550 NA 0.110944309 0.0025869926 -0.142274244
## EP_LIMENG 0.501773188 NA 0.076570341 -0.0543647464 0.213566081
## EP_MOBILE -0.105151665 NA -0.110947714 -0.0177569198 0.026745213
## EP_GROUPQ -0.011596357 NA -0.025805224 0.0812986482 -0.041434379
## EP_BPHIGH 0.098169139 NA 0.140038830 -0.0727846350 -0.250923924
## EP_ASTHMA 0.357270970 NA 0.147105825 -0.0400409764 -0.176451154
## EP_CANCER -0.475770473 NA -0.157067461 -0.0624671550 -0.082100267
## EP_MHLTH 0.563466839 NA 0.229193606 -0.0006942556 -0.057912276
## EP_DIABETES 0.492449837 NA 0.277342878 -0.0446842377 -0.148317377
## EPL_BPHIGH 0.124736144 NA 0.171105837 -0.0860034297 -0.280163993
## EPL_ASTHMA 0.430747858 NA 0.171740467 -0.0180318128 -0.094470649
## EPL_CANCER -0.483951306 NA -0.149267601 -0.0503484066 -0.070497106
## EPL_DIABETES 0.502676740 NA 0.279105992 -0.0344711114 -0.102161803
## EPL_MHLTH 0.586378386 NA 0.225229181 0.0085251856 -0.033777127
## E_COAL E_LEAD E_PARK E_HOUAGE E_WLKIND
## E_TOTPOP NA NA -0.018091031 0.027762532 -0.2751500540
## M_TOTPOP NA NA -0.036007141 -0.002710476 -0.2752648540
## E_DAYPOP NA NA -0.036973389 -0.052177602 -0.0641518142
## SPL_EJI NA NA 0.218104212 -0.159236163 -0.1611858193
## RPL_EJI NA NA 0.262178305 -0.136864795 -0.1383090834
## SPL_SER NA NA 0.262898630 -0.098564112 -0.1225574543
## RPL_SER NA NA 0.314583104 -0.092205212 -0.0911679521
## EPL_OZONE NA NA -0.101678695 0.241367312 0.0063469283
## EPL_PM NA NA 0.237439544 0.182853726 0.0265260362
## EPL_DSLPM NA NA 0.446641296 -0.164459625 0.0257900038
## EPL_TOTCR NA NA 0.458094615 -0.258226236 0.0182992622
## SPL_EBM_THEME1 NA NA 0.522622861 0.091533612 0.0432316209
## RPL_EBM_DOM1 NA NA 0.486470510 0.101469322 0.0343771653
## EPL_NPL NA NA NA NA NA
## EPL_TRI NA NA 0.115558251 -0.251081371 0.0563431990
## EPL_TSD NA NA 0.004169828 -0.123534763 -0.0815413585
## EPL_RMP NA NA 0.031696072 0.148042179 -0.0167060453
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 NA NA 0.138226307 -0.133727587 0.0289924616
## RPL_EBM_DOM2 NA NA 0.150429971 -0.124291225 0.0495021940
## EPL_PARK NA NA -0.997432555 -0.007147892 -0.0901295345
## EPL_HOUAGE NA NA 0.012842041 0.997562969 -0.1566066814
## EPL_WLKIND NA NA -0.089382230 0.158256135 -0.9953438933
## SPL_EBM_THEME3 NA NA -0.100204590 0.838897768 -0.6630361723
## RPL_EBM_DOM3 NA NA -0.108892696 0.781416145 -0.6921184423
## EPL_RAIL NA NA 0.403688457 0.032401785 0.0525332681
## EPL_ROAD NA NA 0.644229595 0.148252840 0.0733929824
## EPL_AIRPRT NA NA 0.007240964 -0.006907803 -0.0880445530
## SPL_EBM_THEME4 NA NA 0.550009416 0.071920948 0.0239000720
## RPL_EBM_DOM4 NA NA 0.527299069 0.072984866 0.0281603395
## EPL_IMPWTR NA NA 0.390603779 -0.107718561 -0.0083874804
## SPL_EBM_THEME5 NA NA 0.390603779 -0.107718561 -0.0083874804
## RPL_EBM_DOM5 NA NA 0.390650918 -0.107543088 -0.0083489281
## SPL_EBM NA NA 0.315631028 0.298169934 -0.2658539079
## RPL_EBM NA NA 0.419074057 0.284599175 -0.2155993073
## EPL_MINRTY NA NA 0.161626471 -0.204085839 -0.1220662675
## SPL_SVM_DOM1 NA NA 0.161626471 -0.204085839 -0.1220662675
## RPL_SVM_DOM1 NA NA 0.161626471 -0.204085839 -0.1220662675
## EPL_POV200 NA NA 0.144226754 -0.249085229 -0.0670290120
## EPL_NOHSDP NA NA 0.188884207 -0.216390227 -0.0438060945
## EPL_UNEMP NA NA 0.060438847 -0.064479283 -0.1175319193
## EPL_RENTER NA NA 0.143563432 -0.136342747 -0.0521414568
## EPL_HOUBDN NA NA 0.081195126 -0.156954656 -0.0304355166
## EPL_UNINSUR NA NA 0.044738461 -0.072719057 0.0087344221
## EPL_NOINT NA NA 0.074879329 -0.265405142 -0.0954537020
## SPL_SVM_DOM2 NA NA 0.133304733 -0.216065206 -0.0769789331
## RPL_SVM_DOM2 NA NA 0.138454732 -0.206363607 -0.0711808633
## EPL_AGE65 NA NA -0.092165331 0.228025991 -0.0112502191
## EPL_AGE17 NA NA 0.102211970 -0.288012053 -0.0114353736
## EPL_DISABL NA NA -0.048113645 -0.070055629 -0.0722130882
## EPL_LIMENG NA NA 0.117480690 -0.161746848 0.0016471087
## SPL_SVM_DOM3 NA NA 0.022142625 -0.146502961 -0.0579208291
## RPL_SVM_DOM3 NA NA 0.035555810 -0.154431024 -0.0477974556
## EPL_MOBILE NA NA 0.029747537 0.109873059 -0.0189738335
## EPL_GROUPQ NA NA -0.028793340 -0.214154297 0.1131989571
## SPL_SVM_DOM4 NA NA -0.010373951 -0.131306842 0.0884180768
## RPL_SVM_DOM4 NA NA -0.008384719 -0.129228614 0.0896057643
## SPL_SVM NA NA 0.118976690 -0.258519848 -0.0603188086
## RPL_SVM NA NA 0.125929006 -0.242810583 -0.0497443196
## F_BPHIGH NA NA 0.063723217 -0.036507017 -0.1465279996
## F_ASTHMA NA NA 0.178982298 -0.133275474 -0.1283591416
## F_CANCER NA NA -0.135722748 0.171889926 0.0224062502
## F_MHLTH NA NA 0.082852704 -0.290704279 -0.0778944818
## F_DIABETES NA NA 0.155704592 -0.128067804 -0.0993958993
## F_HVM NA NA 0.133819085 -0.178011892 -0.1605930104
## RPL_HVM NA NA 0.133819085 -0.178011892 -0.1605930104
## E_OZONE NA NA -0.150147910 0.213870444 0.0017513620
## E_PM NA NA 0.247116334 0.178208415 0.0310963569
## E_DSLPM NA NA 0.172488307 -0.162748579 -0.0041896037
## E_TOTCR NA NA 0.293170497 -0.281333327 -0.0131316070
## E_NPL NA NA NA NA NA
## E_TRI NA NA 0.102294766 -0.264221452 0.0707528090
## E_TSD NA NA 0.004169828 -0.123534763 -0.0815413585
## E_RMP NA NA 0.026697525 0.163771047 -0.0269130077
## E_COAL 1 NA NA NA NA
## E_LEAD NA 1 NA NA NA
## E_PARK NA NA 1.000000000 0.010097885 0.0890920478
## E_HOUAGE NA NA 0.010097885 1.000000000 -0.1595274587
## E_WLKIND NA NA 0.089092048 -0.159527459 1.0000000000
## E_RAIL NA NA 0.370926232 0.052862018 0.0640701969
## E_ROAD NA NA 0.553927127 0.146947908 0.0720027104
## E_AIRPRT NA NA 0.004885500 -0.005192267 -0.0160546079
## E_IMPWTR NA NA 0.514945430 -0.081072237 0.0003961643
## EP_MINRTY NA NA 0.174900225 -0.197085830 -0.1228292699
## EP_POV200 NA NA 0.124065167 -0.262985508 -0.1024941867
## EP_NOHSDP NA NA 0.132778403 -0.207572290 -0.0968197460
## EP_UNEMP NA NA 0.066557412 -0.064144904 -0.1316541482
## EP_RENTER NA NA 0.139101194 -0.161010609 -0.0730249182
## EP_HOUBDN NA NA 0.097551511 -0.136289318 -0.0474805539
## EP_UNINSUR NA NA 0.046437992 -0.058283821 -0.0097354660
## EP_NOINT NA NA 0.070289565 -0.253295521 -0.1328642265
## EP_AGE65 NA NA -0.065564646 0.218916248 -0.0494098577
## EP_AGE17 NA NA 0.088669901 -0.280812713 -0.0364069245
## EP_DISABL NA NA -0.035502946 -0.004382962 -0.0987765550
## EP_LIMENG NA NA 0.100437363 -0.032847291 -0.0161535954
## EP_MOBILE NA NA 0.024360245 0.110953861 0.0039022652
## EP_GROUPQ NA NA -0.062427139 -0.041930902 0.0170798704
## EP_BPHIGH NA NA 0.081805948 -0.034089585 -0.2052365868
## EP_ASTHMA NA NA 0.119067213 -0.227030924 -0.1831507460
## EP_CANCER NA NA -0.111592327 0.217404733 -0.0405961420
## EP_MHLTH NA NA 0.111815320 -0.269612132 -0.1075181900
## EP_DIABETES NA NA 0.134668041 -0.212234434 -0.2146196585
## EPL_BPHIGH NA NA 0.088375857 -0.057226132 -0.1937361736
## EPL_ASTHMA NA NA 0.156692212 -0.202729943 -0.1214098872
## EPL_CANCER NA NA -0.132620969 0.231142187 -0.0139639427
## EPL_DIABETES NA NA 0.192718830 -0.180137082 -0.1674611259
## EPL_MHLTH NA NA 0.125139932 -0.273423242 -0.0690850487
## E_RAIL E_ROAD E_AIRPRT E_IMPWTR
## E_TOTPOP 0.074087957 -0.019435221 0.034347987 0.0190838127
## M_TOTPOP 0.069866006 -0.069885206 0.077884929 0.0404943628
## E_DAYPOP 0.043575517 -0.160865578 0.423779728 -0.0364608652
## SPL_EJI 0.418816771 0.057853631 0.056042715 0.4833550385
## RPL_EJI 0.489642955 0.085331807 0.048252223 0.4994514849
## SPL_SER 0.454655877 0.071480558 0.086134704 0.5563821775
## RPL_SER 0.502503469 0.119991233 0.058433021 0.5740878567
## EPL_OZONE -0.270381925 -0.043178952 -0.010156132 -0.2024118002
## EPL_PM 0.565792846 0.204695478 -0.057491405 0.0581830287
## EPL_DSLPM 0.307862072 0.265776912 0.011710200 0.6276467354
## EPL_TOTCR 0.253592605 0.206688115 0.053634173 0.6247023342
## SPL_EBM_THEME1 0.183724485 0.293575534 0.020483127 0.5346390781
## RPL_EBM_DOM1 0.160536284 0.269314204 0.024817888 0.5111686204
## EPL_NPL NA NA NA NA
## EPL_TRI 0.123387513 -0.011489750 0.048014694 0.2355656734
## EPL_TSD 0.012783337 0.005633601 -0.003561189 0.0223267351
## EPL_RMP 0.089576305 -0.089957477 0.161622584 -0.0465613601
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.195542280 -0.085836689 0.181412698 0.1902723095
## RPL_EBM_DOM2 0.202355984 -0.045055195 0.133659634 0.1900606401
## EPL_PARK -0.376793799 -0.528494556 -0.004962782 -0.4974012484
## EPL_HOUAGE 0.051542890 0.146240353 -0.008759735 -0.0785259312
## EPL_WLKIND -0.068546488 -0.070213899 0.018988991 0.0011482188
## SPL_EBM_THEME3 -0.021421010 0.039863419 0.003362697 -0.0893638222
## RPL_EBM_DOM3 -0.020773412 0.009945518 -0.001980974 -0.0768111571
## EPL_RAIL 0.982560660 0.208880229 -0.007349412 0.2480418549
## EPL_ROAD 0.232124051 0.986632235 -0.253401025 0.3863714739
## EPL_AIRPRT -0.013332872 -0.610772148 0.696711800 0.0363838780
## SPL_EBM_THEME4 0.887423579 0.192047816 0.257784521 0.3507440539
## RPL_EBM_DOM4 0.932417418 0.230782285 0.142780963 0.3303455804
## EPL_IMPWTR 0.222472698 0.217957780 0.032995082 0.9645099347
## SPL_EBM_THEME5 0.222472698 0.217957780 0.032995082 0.9645099347
## RPL_EBM_DOM5 0.222557343 0.218058541 0.032945014 0.9645681377
## SPL_EBM 0.460084564 0.061381369 0.224415683 0.3502586149
## RPL_EBM 0.552527315 0.216303328 0.114129722 0.4064077563
## EPL_MINRTY 0.224978365 0.016591350 0.031752797 0.5560419998
## SPL_SVM_DOM1 0.224978365 0.016591350 0.031752797 0.5560419998
## RPL_SVM_DOM1 0.224978365 0.016591350 0.031752797 0.5560419998
## EPL_POV200 0.265309855 0.019571889 0.052821764 0.5357739836
## EPL_NOHSDP 0.215402333 0.078193343 0.042725974 0.5599925009
## EPL_UNEMP 0.153752636 -0.032241031 0.035555076 0.2491193305
## EPL_RENTER 0.335603450 0.068795742 0.030787229 0.3823412044
## EPL_HOUBDN 0.292044171 0.008282391 0.036161091 0.5365354468
## EPL_UNINSUR 0.246304611 0.001219040 0.057237906 0.3510801480
## EPL_NOINT 0.189323769 -0.026211452 0.065676828 0.2807924438
## SPL_SVM_DOM2 0.312085288 0.016260844 0.061366016 0.5311118459
## RPL_SVM_DOM2 0.318876174 0.017898654 0.051266833 0.5414783521
## EPL_AGE65 -0.159355556 -0.073621876 -0.040039180 -0.4769143563
## EPL_AGE17 0.130579210 0.002841175 0.027102960 0.3766639686
## EPL_DISABL -0.194513651 -0.105047266 -0.059038197 0.0295618348
## EPL_LIMENG 0.162459932 0.031736323 0.042387505 0.3908301863
## SPL_SVM_DOM3 -0.074569775 -0.101164434 -0.028361478 0.0872147827
## RPL_SVM_DOM3 -0.049730517 -0.076058071 -0.025202289 0.0992291658
## EPL_MOBILE 0.052081305 -0.002509688 -0.003836879 0.0017187287
## EPL_GROUPQ 0.119223428 -0.023696775 0.065136717 -0.0594214485
## SPL_SVM_DOM4 0.128159809 -0.021660406 0.054319955 -0.0504198931
## RPL_SVM_DOM4 0.126936644 -0.011104786 0.063168157 -0.0590291529
## SPL_SVM 0.273820661 -0.019151010 0.057199612 0.4635354886
## RPL_SVM 0.294041706 -0.011087012 0.051520261 0.4792782504
## F_BPHIGH 0.098341344 0.039831150 -0.040987165 0.0095472071
## F_ASTHMA 0.282193692 0.055582646 0.027295996 0.5037679742
## F_CANCER -0.038519297 -0.076509439 -0.021167024 -0.4881215069
## F_MHLTH 0.182207596 0.017231686 0.052318568 0.3489043528
## F_DIABETES 0.318249882 0.037167616 0.031376724 0.4118288563
## F_HVM 0.300124746 0.033995658 0.018403273 0.3191379935
## RPL_HVM 0.300124746 0.033995658 0.018403273 0.3191379935
## E_OZONE -0.341726076 -0.059444793 -0.027292896 -0.2645983146
## E_PM 0.582616129 0.208791649 -0.056431360 0.0689636932
## E_DSLPM 0.213732633 0.083657771 -0.002134779 0.4453743903
## E_TOTCR 0.206906554 0.092646453 0.055497997 0.5286825454
## E_NPL NA NA NA NA
## E_TRI 0.151778824 -0.015555368 0.054573291 0.2653670871
## E_TSD 0.012783337 0.005633601 -0.003561189 0.0223267351
## E_RMP 0.078709372 -0.052206246 0.180050200 -0.0398094308
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.370926232 0.553927127 0.004885500 0.5149454296
## E_HOUAGE 0.052862018 0.146947908 -0.005192267 -0.0810722369
## E_WLKIND 0.064070197 0.072002710 -0.016054608 0.0003961643
## E_RAIL 1.000000000 0.202077335 -0.003883841 0.2346513393
## E_ROAD 0.202077335 1.000000000 -0.291419713 0.3253870460
## E_AIRPRT -0.003883841 -0.291419713 1.000000000 0.0257640795
## E_IMPWTR 0.234651339 0.325387046 0.025764080 1.0000000000
## EP_MINRTY 0.243811335 0.025612689 0.032602139 0.5666799195
## EP_POV200 0.240156672 -0.001654406 0.059297937 0.4693750961
## EP_NOHSDP 0.217025680 0.063786990 0.048803842 0.4502718348
## EP_UNEMP 0.160411787 -0.012198977 0.009804192 0.2461094652
## EP_RENTER 0.327602795 0.062045134 0.032920399 0.4236766631
## EP_HOUBDN 0.295377215 0.023606821 0.039677496 0.4648505047
## EP_UNINSUR 0.224737735 0.021055540 0.053033483 0.3196895994
## EP_NOINT 0.149363779 -0.012870416 0.066921450 0.2468181423
## EP_AGE65 -0.110413477 -0.041389092 -0.035967571 -0.4834718931
## EP_AGE17 0.114002270 0.004661401 0.013993217 0.3218020914
## EP_DISABL -0.168114775 -0.078241394 -0.042340454 0.0315238045
## EP_LIMENG 0.224590499 0.061444589 0.044295334 0.3758062938
## EP_MOBILE 0.029755166 -0.019099036 0.003339210 -0.0649976609
## EP_GROUPQ 0.008218480 0.013379770 0.059383290 -0.1259261286
## EP_BPHIGH 0.145192849 -0.009674720 -0.027268319 0.0483327564
## EP_ASTHMA 0.236839403 0.034635043 0.012102655 0.3550221687
## EP_CANCER -0.186202155 -0.030550952 -0.065874381 -0.5817662133
## EP_MHLTH 0.222357516 0.028342338 0.059769537 0.4643366152
## EP_DIABETES 0.205241857 0.005383470 0.007667649 0.3406190388
## EPL_BPHIGH 0.162640113 0.002986434 -0.026457350 0.0764583398
## EPL_ASTHMA 0.270066113 0.059461724 0.028819762 0.5137565951
## EPL_CANCER -0.206910366 -0.046204590 -0.054624121 -0.5863327493
## EPL_DIABETES 0.258419432 0.031817876 0.025268038 0.4627063273
## EPL_MHLTH 0.246098162 0.038189646 0.059351475 0.5173792224
## EP_MINRTY EP_POV200 EP_NOHSDP EP_UNEMP EP_RENTER
## E_TOTPOP 0.223953727 0.180564658 0.14211611 0.108648338 0.233875973
## M_TOTPOP 0.272221808 0.207334560 0.18151960 0.119303604 0.243624730
## E_DAYPOP 0.021597292 0.115987510 0.01116680 0.070496684 0.151737335
## SPL_EJI 0.715317565 0.805142223 0.75522721 0.449828229 0.728646914
## RPL_EJI 0.721970354 0.767671292 0.71461607 0.416421286 0.708230402
## SPL_SER 0.655630195 0.802046644 0.74086755 0.469446575 0.772183916
## RPL_SER 0.649215821 0.762280007 0.70002449 0.438038552 0.745425512
## EPL_OZONE -0.270100626 -0.476235305 -0.44737009 -0.215711481 -0.526610629
## EPL_PM 0.126112071 0.116415163 0.10273188 0.127250113 0.268508283
## EPL_DSLPM 0.464074247 0.572094493 0.55716919 0.265522974 0.577875001
## EPL_TOTCR 0.463186391 0.597512110 0.55717208 0.270545758 0.560715718
## SPL_EBM_THEME1 0.267715739 0.151260337 0.14114222 0.097893937 0.106881266
## RPL_EBM_DOM1 0.251503422 0.130632898 0.12658537 0.088992811 0.085732156
## EPL_NPL NA NA NA NA NA
## EPL_TRI 0.184168508 0.212476186 0.21505105 0.020096240 0.102321951
## EPL_TSD 0.001753528 0.009679261 -0.03791915 0.008259653 0.028542440
## EPL_RMP -0.078913526 0.000980073 -0.06996051 0.025005213 0.116686274
## EPL_COAL NA NA NA NA NA
## EPL_LEAD NA NA NA NA NA
## SPL_EBM_THEME2 0.110908365 0.206298440 0.14269613 0.041439288 0.200221472
## RPL_EBM_DOM2 0.127452928 0.223847971 0.16904291 0.032612698 0.220206609
## EPL_PARK -0.178276677 -0.126106496 -0.13406281 -0.067780865 -0.142212961
## EPL_HOUAGE -0.201077156 -0.270817768 -0.21988809 -0.073034636 -0.167462954
## EPL_WLKIND 0.119595305 0.095792529 0.09536510 0.128308888 0.068226603
## SPL_EBM_THEME3 -0.098110592 -0.160474043 -0.12272107 0.010151329 -0.098319500
## RPL_EBM_DOM3 -0.079356606 -0.143165814 -0.12169345 0.022783567 -0.088902970
## EPL_RAIL 0.245553961 0.240083811 0.21567111 0.149539032 0.318756673
## EPL_ROAD 0.043214166 0.015255261 0.07532014 0.001623777 0.073781226
## EPL_AIRPRT 0.052000861 0.060805851 0.01816487 0.041302017 0.003309397
## SPL_EBM_THEME4 0.244476051 0.235178001 0.21323183 0.145618396 0.291193863
## RPL_EBM_DOM4 0.246800228 0.231240594 0.21436155 0.149535452 0.297564798
## EPL_IMPWTR 0.603605225 0.528188603 0.50193822 0.255942547 0.483602366
## SPL_EBM_THEME5 0.603605225 0.528188603 0.50193822 0.255942547 0.483602366
## RPL_EBM_DOM5 0.603551054 0.528168626 0.50189420 0.255858372 0.483671111
## SPL_EBM 0.197019637 0.219969874 0.17941573 0.115067258 0.253801984
## RPL_EBM 0.237896620 0.247593993 0.22181227 0.118962964 0.286299757
## EPL_MINRTY 0.995594477 0.622923193 0.59011516 0.346038596 0.511884310
## SPL_SVM_DOM1 0.995594477 0.622923193 0.59011516 0.346038596 0.511884310
## RPL_SVM_DOM1 0.995594477 0.622923193 0.59011516 0.346038596 0.511884310
## EPL_POV200 0.699389906 0.962636535 0.81515776 0.485332626 0.855339974
## EPL_NOHSDP 0.671810519 0.789297703 0.89010765 0.353634146 0.705953703
## EPL_UNEMP 0.355215732 0.459654871 0.39329701 0.815656456 0.400236391
## EPL_RENTER 0.447194644 0.737541725 0.62691282 0.277468791 0.952920983
## EPL_HOUBDN 0.693796342 0.749919877 0.63964664 0.423839650 0.707977905
## EPL_UNINSUR 0.365336649 0.406081568 0.39796690 0.218873305 0.455959351
## EPL_NOINT 0.466658065 0.565357796 0.56208953 0.238810979 0.536337823
## SPL_SVM_DOM2 0.681938934 0.865320329 0.79451210 0.542080680 0.846785901
## RPL_SVM_DOM2 0.694718891 0.845418118 0.76958656 0.506707478 0.838897054
## EPL_AGE65 -0.587461715 -0.627577679 -0.53200046 -0.353566889 -0.654070040
## EPL_AGE17 0.560806123 0.725615033 0.63489715 0.351648183 0.618614027
## EPL_DISABL 0.029878577 0.173197283 0.19102235 0.152716853 0.091150194
## EPL_LIMENG 0.474211394 0.611611713 0.63059391 0.246581333 0.639920566
## SPL_SVM_DOM3 0.173917982 0.398251434 0.41622828 0.179911005 0.260907415
## RPL_SVM_DOM3 0.181396786 0.407556903 0.41359856 0.181749673 0.281777234
## EPL_MOBILE -0.029269078 -0.043131435 -0.03006588 -0.046898538 -0.047905474
## EPL_GROUPQ -0.017224233 0.139053511 0.12050549 0.185275699 0.101072539
## SPL_SVM_DOM4 -0.029087073 0.098974784 0.08932785 0.137013450 0.063892308
## RPL_SVM_DOM4 -0.045112345 0.091404717 0.08542296 0.142291351 0.053082257
## SPL_SVM 0.646267340 0.849218095 0.79437827 0.530441183 0.778933773
## RPL_SVM 0.671493670 0.840684271 0.77961141 0.503555508 0.788161276
## F_BPHIGH 0.283721500 0.137059784 0.15309647 0.102892018 0.009928528
## F_ASTHMA 0.693464970 0.606038074 0.53787372 0.281216646 0.566734807
## F_CANCER -0.670695133 -0.474425421 -0.45135385 -0.264346404 -0.430514803
## F_MHLTH 0.495137885 0.758301875 0.73109764 0.427835848 0.699318372
## F_DIABETES 0.740003586 0.589401264 0.55926620 0.287701378 0.524497204
## F_HVM 0.616581177 0.638886829 0.60913202 0.338581314 0.538332035
## RPL_HVM 0.616581177 0.638886829 0.60913202 0.338581314 0.538332035
## E_OZONE -0.290945153 -0.516850942 -0.47652741 -0.264131973 -0.600397803
## E_PM 0.135365945 0.124334352 0.11171290 0.132969447 0.273798669
## E_DSLPM 0.429323448 0.553668597 0.53820635 0.245409162 0.577471189
## E_TOTCR 0.456302190 0.611149172 0.56436769 0.272112537 0.575049960
## E_NPL NA NA NA NA NA
## E_TRI 0.218911982 0.230228651 0.23895994 0.020956590 0.148549515
## E_TSD 0.001753528 0.009679261 -0.03791915 0.008259653 0.028542440
## E_RMP -0.041209450 0.025828865 -0.03338917 -0.027625828 0.152099146
## E_COAL NA NA NA NA NA
## E_LEAD NA NA NA NA NA
## E_PARK 0.174900225 0.124065167 0.13277840 0.066557412 0.139101194
## E_HOUAGE -0.197085830 -0.262985508 -0.20757229 -0.064144904 -0.161010609
## E_WLKIND -0.122829270 -0.102494187 -0.09681975 -0.131654148 -0.073024918
## E_RAIL 0.243811335 0.240156672 0.21702568 0.160411787 0.327602795
## E_ROAD 0.025612689 -0.001654406 0.06378699 -0.012198977 0.062045134
## E_AIRPRT 0.032602139 0.059297937 0.04880384 0.009804192 0.032920399
## E_IMPWTR 0.566679919 0.469375096 0.45027183 0.246109465 0.423676663
## EP_MINRTY 1.000000000 0.622085632 0.58815215 0.337975636 0.515741585
## EP_POV200 0.622085632 1.000000000 0.83685287 0.509812541 0.832681029
## EP_NOHSDP 0.588152153 0.836852872 1.00000000 0.410259219 0.719133692
## EP_UNEMP 0.337975636 0.509812541 0.41025922 1.000000000 0.366292284
## EP_RENTER 0.515741585 0.832681029 0.71913369 0.366292284 1.000000000
## EP_HOUBDN 0.581458454 0.790594313 0.63766735 0.504472595 0.685620205
## EP_UNINSUR 0.329459281 0.390526504 0.38218079 0.205975113 0.434073198
## EP_NOINT 0.433352243 0.557117887 0.56557149 0.214426539 0.511024331
## EP_AGE65 -0.593289077 -0.560591847 -0.49839048 -0.290855292 -0.601155320
## EP_AGE17 0.527549320 0.674249337 0.60444972 0.280190603 0.568509770
## EP_DISABL -0.039213762 0.208863432 0.14082108 0.239441903 0.075144459
## EP_LIMENG 0.442701988 0.625279035 0.65837782 0.246951368 0.674528583
## EP_MOBILE -0.044307759 -0.090205065 -0.06351061 -0.077972558 -0.093511493
## EP_GROUPQ -0.275186510 0.013493651 -0.08396543 0.124535278 -0.059750400
## EP_BPHIGH 0.335166391 0.201301233 0.19237009 0.118565006 0.020432651
## EP_ASTHMA 0.650352420 0.690197977 0.65162902 0.393695141 0.514720440
## EP_CANCER -0.708854632 -0.646563833 -0.57517976 -0.384888851 -0.645130840
## EP_MHLTH 0.622777948 0.904031263 0.85086180 0.484325597 0.778273949
## EP_DIABETES 0.627310667 0.755489723 0.70934240 0.325431918 0.555682374
## EPL_BPHIGH 0.377817502 0.228223093 0.23468259 0.136588044 0.052375316
## EPL_ASTHMA 0.773573053 0.698843216 0.66289322 0.362276417 0.582520321
## EPL_CANCER -0.759139564 -0.664509597 -0.60155522 -0.394789591 -0.655729134
## EPL_DIABETES 0.795432987 0.719176733 0.69024580 0.341321926 0.573364536
## EPL_MHLTH 0.664455175 0.909615572 0.85160069 0.490498089 0.818879607
## EP_HOUBDN EP_UNINSUR EP_NOINT EP_AGE65
## E_TOTPOP 0.049183523 0.178761415 0.090422389 -0.160133244
## M_TOTPOP 0.089727934 0.226720802 0.121999506 -0.195020522
## E_DAYPOP 0.039455670 0.066084694 0.043346061 0.006000718
## SPL_EJI 0.639389119 0.387141230 0.625370322 -0.421463367
## RPL_EJI 0.639001419 0.397788252 0.578503713 -0.412061868
## SPL_SER 0.701270446 0.490432859 0.542340487 -0.496968905
## RPL_SER 0.687581320 0.466539989 0.512276256 -0.478725003
## EPL_OZONE -0.333309272 -0.258590328 -0.317991048 0.294970916
## EPL_PM 0.197937527 0.182253308 0.048810163 -0.111483773
## EPL_DSLPM 0.471330780 0.277092541 0.338068309 -0.414123355
## EPL_TOTCR 0.466621003 0.268981625 0.354365922 -0.399034195
## SPL_EBM_THEME1 0.215942477 0.063182946 0.034703911 -0.153100684
## RPL_EBM_DOM1 0.201161486 0.050521786 0.029634659 -0.137967570
## EPL_NPL NA NA NA NA
## EPL_TRI 0.069158787 0.058407643 0.203403721 -0.076331840
## EPL_TSD -0.007854507 0.093086188 -0.040044952 -0.087748064
## EPL_RMP 0.074778915 0.041250770 -0.148683350 -0.053899001
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.128194901 0.103455870 0.065087803 -0.130575343
## RPL_EBM_DOM2 0.134755502 0.099685162 0.073324698 -0.132023427
## EPL_PARK -0.098877679 -0.050027769 -0.073512125 0.063811507
## EPL_HOUAGE -0.142754999 -0.063239004 -0.265890125 0.221436113
## EPL_WLKIND 0.045879139 0.004066295 0.135831773 0.049173892
## SPL_EBM_THEME3 -0.089087788 -0.048655470 -0.131820188 0.197855550
## RPL_EBM_DOM3 -0.078325270 -0.049572536 -0.130056288 0.187357397
## EPL_RAIL 0.291705328 0.224733153 0.161287424 -0.107242703
## EPL_ROAD 0.037475081 0.019948928 -0.003932019 -0.044907479
## EPL_AIRPRT 0.022602497 0.025230767 0.061010197 0.023845562
## SPL_EBM_THEME4 0.266415927 0.206227649 0.163394217 -0.092106544
## RPL_EBM_DOM4 0.273790985 0.215562806 0.157735648 -0.092902584
## EPL_IMPWTR 0.505527053 0.357324485 0.266850911 -0.528172451
## SPL_EBM_THEME5 0.505527053 0.357324485 0.266850911 -0.528172451
## RPL_EBM_DOM5 0.505577575 0.357338618 0.266825739 -0.528167242
## SPL_EBM 0.207430976 0.161244776 0.070604669 -0.100740715
## RPL_EBM 0.230590189 0.174935622 0.092370725 -0.124100681
## EPL_MINRTY 0.580522652 0.317269945 0.433111048 -0.590787541
## SPL_SVM_DOM1 0.580522652 0.317269945 0.433111048 -0.590787541
## RPL_SVM_DOM1 0.580522652 0.317269945 0.433111048 -0.590787541
## EPL_POV200 0.802502243 0.446655227 0.555505642 -0.632198976
## EPL_NOHSDP 0.654247660 0.426184178 0.514806814 -0.578548447
## EPL_UNEMP 0.445624758 0.330618747 0.203427579 -0.345450769
## EPL_RENTER 0.599710394 0.413978173 0.494332557 -0.566020766
## EPL_HOUBDN 0.862606352 0.429272365 0.423174703 -0.626481160
## EPL_UNINSUR 0.402314805 0.968455679 0.188399432 -0.469799189
## EPL_NOINT 0.375112786 0.220390794 0.960078452 -0.379850241
## SPL_SVM_DOM2 0.762690587 0.614142302 0.616613320 -0.663611832
## RPL_SVM_DOM2 0.762776448 0.580845724 0.589726713 -0.662481501
## EPL_AGE65 -0.567489242 -0.475720654 -0.295302858 0.939372902
## EPL_AGE17 0.557226689 0.334798214 0.375961799 -0.654215416
## EPL_DISABL 0.029323506 -0.126125233 0.325399859 0.138541074
## EPL_LIMENG 0.535687844 0.384148775 0.341412633 -0.467399617
## SPL_SVM_DOM3 0.206353350 -0.035611961 0.372558692 0.110873828
## RPL_SVM_DOM3 0.241858532 0.023305042 0.333245274 0.061580292
## EPL_MOBILE -0.048412730 0.002453157 -0.002906652 -0.002757004
## EPL_GROUPQ 0.101979641 0.084131027 0.091745748 0.044302306
## SPL_SVM_DOM4 0.064428138 0.073762037 0.077724509 0.036873706
## RPL_SVM_DOM4 0.060415822 0.050702065 0.059762992 0.060815807
## SPL_SVM 0.706304441 0.507848804 0.629885792 -0.518689581
## RPL_SVM 0.728806918 0.503636045 0.601700897 -0.533890888
## F_BPHIGH -0.013136033 -0.180993953 0.304196495 0.156648963
## F_ASTHMA 0.555669677 0.389220164 0.410442242 -0.518738602
## F_CANCER -0.471704680 -0.280318677 -0.328978324 0.657504355
## F_MHLTH 0.561064145 0.355622993 0.592429011 -0.523198605
## F_DIABETES 0.510621772 0.283917168 0.438904588 -0.360060555
## F_HVM 0.452022689 0.217079610 0.565581324 -0.268099480
## RPL_HVM 0.452022689 0.217079610 0.565581324 -0.268099480
## E_OZONE -0.393716434 -0.303416318 -0.320083972 0.336395539
## E_PM 0.203297393 0.189278988 0.056686675 -0.117254222
## E_DSLPM 0.463448943 0.286165871 0.335302884 -0.416027133
## E_TOTCR 0.466289861 0.287414223 0.375688335 -0.406619884
## E_NPL NA NA NA NA
## E_TRI 0.094195894 0.102280627 0.222311956 -0.118070996
## E_TSD -0.007854507 0.093086188 -0.040044952 -0.087748064
## E_RMP 0.062734056 0.053447852 -0.140078502 -0.053262827
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.097551511 0.046437992 0.070289565 -0.065564646
## E_HOUAGE -0.136289318 -0.058283821 -0.253295521 0.218916248
## E_WLKIND -0.047480554 -0.009735466 -0.132864227 -0.049409858
## E_RAIL 0.295377215 0.224737735 0.149363779 -0.110413477
## E_ROAD 0.023606821 0.021055540 -0.012870416 -0.041389092
## E_AIRPRT 0.039677496 0.053033483 0.066921450 -0.035967571
## E_IMPWTR 0.464850505 0.319689599 0.246818142 -0.483471893
## EP_MINRTY 0.581458454 0.329459281 0.433352243 -0.593289077
## EP_POV200 0.790594313 0.390526504 0.557117887 -0.560591847
## EP_NOHSDP 0.637667347 0.382180794 0.565571486 -0.498390481
## EP_UNEMP 0.504472595 0.205975113 0.214426539 -0.290855292
## EP_RENTER 0.685620205 0.434073198 0.511024331 -0.601155320
## EP_HOUBDN 1.000000000 0.377860348 0.353561781 -0.490761586
## EP_UNINSUR 0.377860348 1.000000000 0.182950221 -0.454156169
## EP_NOINT 0.353561781 0.182950221 1.000000000 -0.308984482
## EP_AGE65 -0.490761586 -0.454156169 -0.308984482 1.000000000
## EP_AGE17 0.483200269 0.272362161 0.384615455 -0.645012454
## EP_DISABL 0.158785768 -0.115711403 0.160509508 0.273840000
## EP_LIMENG 0.568340965 0.472811800 0.319817722 -0.466240002
## EP_MOBILE -0.095821107 -0.017295516 -0.014783973 0.027104254
## EP_GROUPQ 0.085520796 -0.138129783 -0.163981916 0.333607198
## EP_BPHIGH 0.053209499 -0.074640191 0.316236246 0.232955332
## EP_ASTHMA 0.540280019 0.192419998 0.600822541 -0.451441150
## EP_CANCER -0.651810068 -0.449092161 -0.335682285 0.855705989
## EP_MHLTH 0.730607637 0.378433031 0.632819445 -0.644290625
## EP_DIABETES 0.542327534 0.184952948 0.614625275 -0.251075878
## EPL_BPHIGH 0.068323322 -0.057386233 0.351851643 0.177642218
## EPL_ASTHMA 0.586892277 0.361777508 0.543439212 -0.581839120
## EPL_CANCER -0.659821331 -0.443165741 -0.382530207 0.822363244
## EPL_DIABETES 0.544263360 0.326928739 0.531061650 -0.353042416
## EPL_MHLTH 0.738927940 0.444217078 0.626157676 -0.678427601
## EP_AGE17 EP_DISABL EP_LIMENG EP_MOBILE
## E_TOTPOP 0.1828314472 -0.0606119005 0.173441610 -0.0812259110
## M_TOTPOP 0.1957589634 -0.0706051676 0.159041731 -0.0602584160
## E_DAYPOP -0.0711693707 0.0889629683 0.001210396 0.0080282637
## SPL_EJI 0.5238353632 0.1814879602 0.512676896 -0.0449196760
## RPL_EJI 0.4959133064 0.1265223766 0.500632794 -0.0510024916
## SPL_SER 0.5304188066 0.1502062569 0.623337768 0.0158246839
## RPL_SER 0.4929988654 0.1221400939 0.584887716 0.0076454931
## EPL_OZONE -0.3388139400 -0.0588487253 -0.503035148 0.0661825118
## EPL_PM 0.0691672523 -0.1833049001 0.258820646 0.0699303256
## EPL_DSLPM 0.3918029967 0.0445013654 0.591527463 -0.1045551434
## EPL_TOTCR 0.3886084677 0.1203041165 0.496953756 -0.1054677644
## SPL_EBM_THEME1 0.0628862724 -0.0169899389 0.076484393 -0.0177847457
## RPL_EBM_DOM1 0.0525645906 -0.0278662354 0.063262797 -0.0283702838
## EPL_NPL NA NA NA NA
## EPL_TRI 0.1285087372 0.1262139322 0.054913722 -0.0918225481
## EPL_TSD 0.0375029460 0.0025869926 -0.054364746 -0.0177569198
## EPL_RMP -0.0731207353 -0.1354196067 0.158825284 0.0676536140
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.0671654897 0.0078714441 0.178769006 -0.0338174985
## RPL_EBM_DOM2 0.0749208067 0.0061575613 0.215796902 -0.0371718770
## EPL_PARK -0.0931617848 0.0320558824 -0.102288713 -0.0247455920
## EPL_HOUAGE -0.2844206813 -0.0106727207 -0.034525574 0.1107001883
## EPL_WLKIND 0.0344459547 0.0977588422 0.012062339 -0.0014088667
## SPL_EBM_THEME3 -0.2019504945 0.0468686926 -0.025854129 0.0813401555
## RPL_EBM_DOM3 -0.1927022334 0.0587228735 -0.023001059 0.0772961153
## EPL_RAIL 0.1142019152 -0.1623750581 0.214869618 0.0410933559
## EPL_ROAD 0.0125814695 -0.0766596544 0.069434554 -0.0085633010
## EPL_AIRPRT -0.0002123141 0.0003691784 0.018087723 0.0837409606
## SPL_EBM_THEME4 0.0991117458 -0.1600617112 0.210605591 0.0730878969
## RPL_EBM_DOM4 0.1023910201 -0.1663419547 0.214800524 0.0614238595
## EPL_IMPWTR 0.3682332383 0.0173317992 0.466531748 -0.0839527065
## SPL_EBM_THEME5 0.3682332383 0.0173317992 0.466531748 -0.0839527065
## RPL_EBM_DOM5 0.3681773063 0.0173274235 0.466601054 -0.0838585108
## SPL_EBM 0.0317158284 -0.0249607044 0.240161818 0.0258304011
## RPL_EBM 0.0611891612 -0.0516869059 0.267309248 0.0193520201
## EPL_MINRTY 0.5284192254 -0.0251828627 0.441997026 -0.0502430014
## SPL_SVM_DOM1 0.5284192254 -0.0251828627 0.441997026 -0.0502430014
## RPL_SVM_DOM1 0.5284192254 -0.0251828627 0.441997026 -0.0502430014
## EPL_POV200 0.6597568296 0.1412820654 0.657259304 -0.0898807976
## EPL_NOHSDP 0.5789129176 0.0945714600 0.622966778 -0.0367030268
## EPL_UNEMP 0.2716076425 0.1100038919 0.294802811 -0.0633587421
## EPL_RENTER 0.5285400425 0.0375545930 0.579524263 -0.0801928114
## EPL_HOUBDN 0.5019677279 0.0580550697 0.541213094 -0.0922114659
## EPL_UNINSUR 0.2741928716 -0.1063405587 0.476583757 -0.0127607343
## EPL_NOINT 0.4236403327 0.1050605502 0.335051340 -0.0057583965
## SPL_SVM_DOM2 0.5971206744 0.0837558487 0.647082606 -0.0705801878
## RPL_SVM_DOM2 0.5793695431 0.0727844772 0.623732623 -0.0682334492
## EPL_AGE65 -0.6382261731 0.1873327394 -0.504651099 0.0534043563
## EPL_AGE17 0.9544676345 -0.0687956051 0.492988342 -0.0699191118
## EPL_DISABL 0.0066115140 0.8142164411 -0.073997968 0.0106645990
## EPL_LIMENG 0.4866894833 -0.0298011118 0.813643588 -0.1927334064
## SPL_SVM_DOM3 0.4235434252 0.5446192695 0.238731110 -0.0733027202
## RPL_SVM_DOM3 0.4475350609 0.4864873628 0.273291849 -0.1009311602
## EPL_MOBILE -0.0421914527 -0.0232520273 -0.012481537 0.8829359823
## EPL_GROUPQ 0.0165497876 0.1095498645 0.103568588 0.0132007567
## SPL_SVM_DOM4 -0.0062369495 0.0831905111 0.083267542 0.4406472939
## RPL_SVM_DOM4 -0.0165714432 0.0891040002 0.069374070 0.4247668243
## SPL_SVM 0.6135718905 0.2302389565 0.619768972 0.0447907507
## RPL_SVM 0.6013828909 0.2008629065 0.620206932 0.0101808625
## F_BPHIGH 0.0109841839 0.2254307017 -0.215586770 0.0106027645
## F_ASTHMA 0.4147315073 0.0410199266 0.366289333 -0.0473696036
## F_CANCER -0.4099132016 0.0561308363 -0.330607818 -0.0664175312
## F_MHLTH 0.5703924493 0.0948883507 0.571819840 -0.0769637196
## F_DIABETES 0.4192993461 0.0286742532 0.390887280 -0.0859193857
## F_HVM 0.4082729994 0.1703170134 0.309939851 -0.0877410580
## RPL_HVM 0.4082729994 0.1703170134 0.309939851 -0.0877410580
## E_OZONE -0.3590823987 -0.0275696617 -0.557231113 0.0535782824
## E_PM 0.0735567868 -0.1811825888 0.261221989 0.0682438976
## E_DSLPM 0.3925155397 0.0511828458 0.625276414 -0.0953785301
## E_TOTCR 0.3999033891 0.1508425500 0.501773188 -0.1051516647
## E_NPL NA NA NA NA
## E_TRI 0.1465748630 0.1109443087 0.076570341 -0.1109477139
## E_TSD 0.0375029460 0.0025869926 -0.054364746 -0.0177569198
## E_RMP -0.0119654092 -0.1422742437 0.213566081 0.0267452130
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.0886699009 -0.0355029459 0.100437363 0.0243602448
## E_HOUAGE -0.2808127128 -0.0043829617 -0.032847291 0.1109538606
## E_WLKIND -0.0364069245 -0.0987765550 -0.016153595 0.0039022652
## E_RAIL 0.1140022697 -0.1681147754 0.224590499 0.0297551660
## E_ROAD 0.0046614008 -0.0782413938 0.061444589 -0.0190990365
## E_AIRPRT 0.0139932168 -0.0423404545 0.044295334 0.0033392104
## E_IMPWTR 0.3218020914 0.0315238045 0.375806294 -0.0649976609
## EP_MINRTY 0.5275493195 -0.0392137619 0.442701988 -0.0443077589
## EP_POV200 0.6742493368 0.2088634323 0.625279035 -0.0902050646
## EP_NOHSDP 0.6044497152 0.1408210821 0.658377821 -0.0635106053
## EP_UNEMP 0.2801906027 0.2394419035 0.246951368 -0.0779725583
## EP_RENTER 0.5685097704 0.0751444586 0.674528583 -0.0935114931
## EP_HOUBDN 0.4832002693 0.1587857683 0.568340965 -0.0958211073
## EP_UNINSUR 0.2723621613 -0.1157114029 0.472811800 -0.0172955164
## EP_NOINT 0.3846154554 0.1605095083 0.319817722 -0.0147839729
## EP_AGE65 -0.6450124535 0.2738400003 -0.466240002 0.0271042541
## EP_AGE17 1.0000000000 -0.1663911386 0.449140112 -0.0551118611
## EP_DISABL -0.1663911386 1.0000000000 -0.107695356 -0.0059359505
## EP_LIMENG 0.4491401118 -0.1076953559 1.000000000 -0.0678058170
## EP_MOBILE -0.0551118611 -0.0059359505 -0.067805817 1.0000000000
## EP_GROUPQ -0.3430253985 0.3966217799 -0.154040903 0.0023527312
## EP_BPHIGH 0.0631092290 0.2863474958 -0.152441609 -0.0323865243
## EP_ASTHMA 0.5453755514 0.1061160345 0.225167676 -0.0018987565
## EP_CANCER -0.5414308247 0.1080095821 -0.551081379 0.0027916260
## EP_MHLTH 0.6810220373 0.0955014640 0.572740971 -0.0560053854
## EP_DIABETES 0.4979448162 0.2295425910 0.387385409 -0.0558673560
## EPL_BPHIGH 0.0989761810 0.2534168419 -0.127837342 -0.0375804254
## EPL_ASTHMA 0.5105388842 0.0836719733 0.357103631 -0.0004207458
## EPL_CANCER -0.5568551958 0.1015794376 -0.561798974 -0.0032950301
## EPL_DIABETES 0.5208669012 0.1596349935 0.454890833 -0.0906382134
## EPL_MHLTH 0.6724877560 0.1088215395 0.613874037 -0.0550985764
## EP_GROUPQ EP_BPHIGH EP_ASTHMA EP_CANCER
## E_TOTPOP -0.1074750036 0.090970931 0.138921307 -0.144992129
## M_TOTPOP -0.1175571725 0.120146853 0.185651234 -0.179400052
## E_DAYPOP 0.2951054679 -0.015970754 0.013695233 -0.068758742
## SPL_EJI -0.0400331281 0.503024027 0.763426251 -0.511763363
## RPL_EJI -0.0450446444 0.483819345 0.726552279 -0.504149055
## SPL_SER -0.0510977039 0.163845732 0.539725918 -0.626881685
## RPL_SER -0.0560700777 0.168318182 0.525440594 -0.606695626
## EPL_OZONE -0.0009120689 -0.074181122 -0.271320371 0.299252265
## EPL_PM 0.0131926786 0.058537233 0.158729763 -0.128339430
## EPL_DSLPM -0.0576842727 0.056369495 0.329583370 -0.481525866
## EPL_TOTCR -0.0132756646 0.071758197 0.333475916 -0.481340262
## SPL_EBM_THEME1 -0.0252957191 0.008750381 0.114799784 -0.252373655
## RPL_EBM_DOM1 -0.0314924813 0.001018599 0.096877803 -0.233497560
## EPL_NPL NA NA NA NA
## EPL_TRI -0.0267760123 0.156466898 0.151576180 -0.108669031
## EPL_TSD 0.0812986482 -0.072784635 -0.040040976 -0.062467155
## EPL_RMP 0.0624343397 -0.326134775 -0.195431172 -0.108306518
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.0377957714 -0.133532099 -0.023978069 -0.203903812
## RPL_EBM_DOM2 0.0179592601 -0.122366888 -0.015813661 -0.206628667
## EPL_PARK 0.0724717288 -0.088192505 -0.120552460 0.108154514
## EPL_HOUAGE -0.0475148332 -0.038972928 -0.236022453 0.220545429
## EPL_WLKIND -0.0179291513 0.198859948 0.178258311 0.036137279
## SPL_EBM_THEME3 -0.0411396899 0.072842072 -0.089174274 0.192854436
## RPL_EBM_DOM3 -0.0385948622 0.084283381 -0.081311006 0.178849666
## EPL_RAIL -0.0005683839 0.147016802 0.237582285 -0.187450888
## EPL_ROAD 0.0151211265 -0.005846969 0.044067110 -0.046742023
## EPL_AIRPRT 0.0169751492 -0.019358331 0.003953593 -0.058365324
## SPL_EBM_THEME4 0.0129047392 0.110904273 0.214213706 -0.200402409
## RPL_EBM_DOM4 0.0066379751 0.116794798 0.217379961 -0.196688790
## EPL_IMPWTR -0.1384693183 0.032383417 0.357064552 -0.624860386
## SPL_EBM_THEME5 -0.1384693183 0.032383417 0.357064552 -0.624860386
## RPL_EBM_DOM5 -0.1384460612 0.032343895 0.357028512 -0.624862314
## SPL_EBM -0.0016677168 -0.026078824 0.055526193 -0.209699184
## RPL_EBM -0.0186866442 0.004356150 0.096253707 -0.229591960
## EPL_MINRTY -0.2612818823 0.333833539 0.651027883 -0.703562622
## SPL_SVM_DOM1 -0.2612818823 0.333833539 0.651027883 -0.703562622
## RPL_SVM_DOM1 -0.2612818823 0.333833539 0.651027883 -0.703562622
## EPL_POV200 -0.0572306985 0.139594370 0.647297791 -0.729754810
## EPL_NOHSDP -0.0808544188 0.169073375 0.612624578 -0.644241120
## EPL_UNEMP 0.0423202704 0.088806867 0.341807397 -0.418045311
## EPL_RENTER -0.0986419896 0.010755227 0.453872896 -0.574067220
## EPL_HOUBDN -0.1045455280 0.053308536 0.544902077 -0.736945509
## EPL_UNINSUR -0.1561214206 -0.046125756 0.222088927 -0.473022455
## EPL_NOINT -0.1918389938 0.279097669 0.597730591 -0.399867940
## SPL_SVM_DOM2 -0.1171181192 0.130973624 0.631837055 -0.734557967
## RPL_SVM_DOM2 -0.1245411252 0.130536116 0.626504072 -0.738151970
## EPL_AGE65 0.1659103299 0.181721223 -0.458382794 0.820069046
## EPL_AGE17 -0.2353434536 0.043825068 0.518905754 -0.604051891
## EPL_DISABL 0.0343245252 0.272947579 0.152228816 0.097991449
## EPL_LIMENG -0.1566261053 -0.124388422 0.214571425 -0.513998319
## SPL_SVM_DOM3 -0.0899411169 0.280079929 0.218292851 0.022681463
## RPL_SVM_DOM3 -0.0768505590 0.252877925 0.217301949 -0.000246486
## EPL_MOBILE -0.0238899289 -0.036698905 0.008428629 -0.026708583
## EPL_GROUPQ 0.4137544493 0.017130351 0.033586361 -0.011265996
## SPL_SVM_DOM4 0.3452798473 -0.003065835 0.033068559 -0.022702796
## RPL_SVM_DOM4 0.3903151001 0.001416840 0.024937643 -0.004560913
## SPL_SVM -0.0402050926 0.203123779 0.606990644 -0.622858661
## RPL_SVM -0.0522695124 0.192207242 0.596883525 -0.641107794
## F_BPHIGH 0.0335131393 0.789102666 0.528435094 0.159279150
## F_ASTHMA -0.1366892872 0.333352018 0.651914281 -0.586257668
## F_CANCER 0.2503823200 0.054402192 -0.453387675 0.746400602
## F_MHLTH -0.0587586379 0.180349173 0.662576571 -0.559027121
## F_DIABETES -0.0977804981 0.505785607 0.632864329 -0.435212280
## F_HVM -0.0221177209 0.689213268 0.795662249 -0.305384177
## RPL_HVM -0.0221177209 0.689213268 0.795662249 -0.305384177
## E_OZONE 0.0006549523 -0.010941309 -0.255663904 0.368422565
## E_PM 0.0138148580 0.066549469 0.169701192 -0.136015369
## E_DSLPM -0.0701781240 0.067099159 0.334944469 -0.460212575
## E_TOTCR -0.0115963574 0.098169139 0.357270970 -0.475770473
## E_NPL NA NA NA NA
## E_TRI -0.0258052236 0.140038830 0.147105825 -0.157067461
## E_TSD 0.0812986482 -0.072784635 -0.040040976 -0.062467155
## E_RMP -0.0414343787 -0.250923924 -0.176451154 -0.082100267
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK -0.0624271391 0.081805948 0.119067213 -0.111592327
## E_HOUAGE -0.0419309018 -0.034089585 -0.227030924 0.217404733
## E_WLKIND 0.0170798704 -0.205236587 -0.183150746 -0.040596142
## E_RAIL 0.0082184800 0.145192849 0.236839403 -0.186202155
## E_ROAD 0.0133797700 -0.009674720 0.034635043 -0.030550952
## E_AIRPRT 0.0593832904 -0.027268319 0.012102655 -0.065874381
## E_IMPWTR -0.1259261286 0.048332756 0.355022169 -0.581766213
## EP_MINRTY -0.2751865102 0.335166391 0.650352420 -0.708854632
## EP_POV200 0.0134936506 0.201301233 0.690197977 -0.646563833
## EP_NOHSDP -0.0839654289 0.192370090 0.651629022 -0.575179755
## EP_UNEMP 0.1245352784 0.118565006 0.393695141 -0.384888851
## EP_RENTER -0.0597504000 0.020432651 0.514720440 -0.645130840
## EP_HOUBDN 0.0855207963 0.053209499 0.540280019 -0.651810068
## EP_UNINSUR -0.1381297827 -0.074640191 0.192419998 -0.449092161
## EP_NOINT -0.1639819156 0.316236246 0.600822541 -0.335682285
## EP_AGE65 0.3336071981 0.232955332 -0.451441150 0.855705989
## EP_AGE17 -0.3430253985 0.063109229 0.545375551 -0.541430825
## EP_DISABL 0.3966217799 0.286347496 0.106116035 0.108009582
## EP_LIMENG -0.1540409029 -0.152441609 0.225167676 -0.551081379
## EP_MOBILE 0.0023527312 -0.032386524 -0.001898757 0.002791626
## EP_GROUPQ 1.0000000000 -0.010057283 -0.091329443 0.152250140
## EP_BPHIGH -0.0100572829 1.000000000 0.577337965 0.258749355
## EP_ASTHMA -0.0913294426 0.577337965 1.000000000 -0.464572883
## EP_CANCER 0.1522501403 0.258749355 -0.464572883 1.000000000
## EP_MHLTH -0.0631949783 0.214263911 0.842879638 -0.688146487
## EP_DIABETES -0.0977089683 0.683916765 0.820013704 -0.280260311
## EPL_BPHIGH -0.0266234374 0.976243178 0.622455608 0.194253113
## EPL_ASTHMA -0.1180738087 0.469565733 0.872346264 -0.639614143
## EPL_CANCER 0.1619180165 0.184458754 -0.489951624 0.965149622
## EPL_DIABETES -0.1725101724 0.651814786 0.735848372 -0.405579470
## EPL_MHLTH -0.0626184546 0.195370418 0.790418165 -0.743933368
## EP_MHLTH EP_DIABETES EPL_BPHIGH EPL_ASTHMA
## E_TOTPOP 0.1440892774 0.131260675 0.084142056 0.2002861280
## M_TOTPOP 0.1770018499 0.159736786 0.115766854 0.2598541106
## E_DAYPOP 0.0586769001 0.024572290 -0.020776721 0.0588611062
## SPL_EJI 0.7996123816 0.802809887 0.553117083 0.8315394211
## RPL_EJI 0.7530463670 0.758125195 0.532787761 0.8264365683
## SPL_SER 0.7360947086 0.609860963 0.198726270 0.6604015411
## RPL_SER 0.6974776998 0.581791705 0.201418578 0.6567761702
## EPL_OZONE -0.4388848281 -0.354692458 -0.097868406 -0.2741081652
## EPL_PM 0.1091238862 0.036819009 0.061954722 0.1619784888
## EPL_DSLPM 0.5399321828 0.442053955 0.080803486 0.4082275300
## EPL_TOTCR 0.5450754431 0.470428651 0.097391233 0.4195363015
## SPL_EBM_THEME1 0.1382188594 0.123235831 0.010304047 0.2177790466
## RPL_EBM_DOM1 0.1205034941 0.105066503 0.003616770 0.1972453394
## EPL_NPL NA NA NA NA
## EPL_TRI 0.2180335153 0.279482035 0.185611430 0.1499738207
## EPL_TSD -0.0006942556 -0.044684238 -0.086003430 -0.0180318128
## EPL_RMP -0.0690704509 -0.208489024 -0.348862864 -0.1160224462
## EPL_COAL NA NA NA NA
## EPL_LEAD NA NA NA NA
## SPL_EBM_THEME2 0.1513819708 0.087318000 -0.126421723 0.0441849709
## RPL_EBM_DOM2 0.1651505320 0.113043802 -0.112854794 0.0545006932
## EPL_PARK -0.1114010346 -0.138833019 -0.095711980 -0.1581355925
## EPL_HOUAGE -0.2793621148 -0.219821892 -0.064354407 -0.2116731726
## EPL_WLKIND 0.1028982691 0.206347754 0.186104263 0.1176467572
## SPL_EBM_THEME3 -0.1621732238 -0.062846585 0.046294334 -0.1059292708
## RPL_EBM_DOM3 -0.1557283267 -0.053610275 0.053700478 -0.0940948579
## EPL_RAIL 0.2215591860 0.210288717 0.165095788 0.2737632750
## EPL_ROAD 0.0417640101 0.019643596 0.005512190 0.0732419209
## EPL_AIRPRT 0.0434666764 0.028041631 -0.014129834 0.0181652837
## SPL_EBM_THEME4 0.2197736125 0.195496359 0.132268438 0.2609356239
## RPL_EBM_DOM4 0.2162824386 0.196072548 0.139145500 0.2643480209
## EPL_IMPWTR 0.5043048505 0.374117671 0.066083891 0.5209385688
## SPL_EBM_THEME5 0.5043048505 0.374117671 0.066083891 0.5209385688
## RPL_EBM_DOM5 0.5042753982 0.374051715 0.066053752 0.5209555300
## SPL_EBM 0.1702483863 0.145850895 -0.022415989 0.1376009822
## RPL_EBM 0.2019323453 0.186601223 0.014867519 0.1813343200
## EPL_MINRTY 0.6253997847 0.627575221 0.378010365 0.7658348310
## SPL_SVM_DOM1 0.6253997847 0.627575221 0.378010365 0.7658348310
## RPL_SVM_DOM1 0.6253997847 0.627575221 0.378010365 0.7658348310
## EPL_POV200 0.8702791160 0.690631377 0.175148355 0.7363893384
## EPL_NOHSDP 0.7895720108 0.640517316 0.208937173 0.7301608299
## EPL_UNEMP 0.4430654826 0.290916631 0.109919955 0.3897649849
## EPL_RENTER 0.6890262816 0.486065728 0.038189355 0.5416690744
## EPL_HOUBDN 0.7109944634 0.506674390 0.090262917 0.6941173447
## EPL_UNINSUR 0.3904657389 0.203732536 -0.027962311 0.4056460932
## EPL_NOINT 0.6387604282 0.571126596 0.316224058 0.5849942227
## SPL_SVM_DOM2 0.8373212344 0.625458254 0.170621341 0.7527020196
## RPL_SVM_DOM2 0.8157049096 0.612565720 0.168052005 0.7624194878
## EPL_AGE65 -0.6685355514 -0.288292716 0.138775189 -0.5739665027
## EPL_AGE17 0.6914738444 0.488434639 0.075881806 0.5417651917
## EPL_DISABL 0.1362231866 0.250845085 0.272477293 0.1119228875
## EPL_LIMENG 0.5428927985 0.395586067 -0.089121903 0.3214564985
## SPL_SVM_DOM3 0.2981064809 0.437492693 0.284749840 0.1647525766
## RPL_SVM_DOM3 0.3086577924 0.419857843 0.251995134 0.1673244276
## EPL_MOBILE -0.0229302956 -0.040634871 -0.044941134 0.0141875148
## EPL_GROUPQ 0.1090370357 0.040339341 0.040202084 0.0120765712
## SPL_SVM_DOM4 0.0829045752 0.015040109 0.012828122 0.0173145590
## RPL_SVM_DOM4 0.0730705826 0.008525962 0.015261829 0.0027869666
## SPL_SVM 0.7968560882 0.653536204 0.242940903 0.6906777593
## RPL_SVM 0.7827593274 0.639977352 0.228881622 0.7021937284
## F_BPHIGH 0.1978946402 0.535322627 0.819299560 0.3994579765
## F_ASTHMA 0.6388935921 0.568001434 0.376510839 0.8496561157
## F_CANCER -0.5282930775 -0.325718475 0.012638661 -0.5771807060
## F_MHLTH 0.8235864884 0.617159626 0.238083707 0.6458102768
## F_DIABETES 0.5838711372 0.676220234 0.544935210 0.7544776409
## F_HVM 0.6864854397 0.800334337 0.741880962 0.8042770394
## RPL_HVM 0.6864854397 0.800334337 0.741880962 0.8042770394
## E_OZONE -0.4582178912 -0.329361765 -0.038858606 -0.2840245921
## E_PM 0.1190587576 0.045738146 0.071466719 0.1743674630
## E_DSLPM 0.5365504689 0.431828184 0.094373289 0.3994156479
## E_TOTCR 0.5634668388 0.492449837 0.124736144 0.4307478578
## E_NPL NA NA NA NA
## E_TRI 0.2291936061 0.277342878 0.171105837 0.1717404667
## E_TSD -0.0006942556 -0.044684238 -0.086003430 -0.0180318128
## E_RMP -0.0579122759 -0.148317377 -0.280163993 -0.0944706487
## E_COAL NA NA NA NA
## E_LEAD NA NA NA NA
## E_PARK 0.1118153204 0.134668041 0.088375857 0.1566922116
## E_HOUAGE -0.2696121318 -0.212234434 -0.057226132 -0.2027299434
## E_WLKIND -0.1075181900 -0.214619658 -0.193736174 -0.1214098872
## E_RAIL 0.2223575156 0.205241857 0.162640113 0.2700661126
## E_ROAD 0.0283423378 0.005383470 0.002986434 0.0594617237
## E_AIRPRT 0.0597695373 0.007667649 -0.026457350 0.0288197624
## E_IMPWTR 0.4643366152 0.340619039 0.076458340 0.5137565951
## EP_MINRTY 0.6227779478 0.627310667 0.377817502 0.7735730529
## EP_POV200 0.9040312632 0.755489723 0.228223093 0.6988432160
## EP_NOHSDP 0.8508617971 0.709342396 0.234682588 0.6628932243
## EP_UNEMP 0.4843255973 0.325431918 0.136588044 0.3622764167
## EP_RENTER 0.7782739486 0.555682374 0.052375316 0.5825203208
## EP_HOUBDN 0.7306076368 0.542327534 0.068323322 0.5868922771
## EP_UNINSUR 0.3784330312 0.184952948 -0.057386233 0.3617775079
## EP_NOINT 0.6328194453 0.614625275 0.351851643 0.5434392116
## EP_AGE65 -0.6442906252 -0.251075878 0.177642218 -0.5818391197
## EP_AGE17 0.6810220373 0.497944816 0.098976181 0.5105388842
## EP_DISABL 0.0955014640 0.229542591 0.253416842 0.0836719733
## EP_LIMENG 0.5727409714 0.387385409 -0.127837342 0.3571036313
## EP_MOBILE -0.0560053854 -0.055867356 -0.037580425 -0.0004207458
## EP_GROUPQ -0.0631949783 -0.097708968 -0.026623437 -0.1180738087
## EP_BPHIGH 0.2142639108 0.683916765 0.976243178 0.4695657333
## EP_ASTHMA 0.8428796381 0.820013704 0.622455608 0.8723462641
## EP_CANCER -0.6881464867 -0.280260311 0.194253113 -0.6396141431
## EP_MHLTH 1.0000000000 0.775652225 0.268864418 0.7904896317
## EP_DIABETES 0.7756522245 1.000000000 0.693451554 0.7139582930
## EPL_BPHIGH 0.2688644176 0.693451554 1.000000000 0.5213586789
## EPL_ASTHMA 0.7904896317 0.713958293 0.521358679 1.0000000000
## EPL_CANCER -0.6938276299 -0.330158236 0.123182926 -0.6533598507
## EPL_DIABETES 0.6979786895 0.874710277 0.681018166 0.8091343282
## EPL_MHLTH 0.9681341996 0.725279743 0.253046530 0.8259283987
## EPL_CANCER EPL_DIABETES EPL_MHLTH
## E_TOTPOP -0.143152608 0.21414647 0.168604433
## M_TOTPOP -0.182268395 0.26231020 0.213508039
## E_DAYPOP -0.041446714 0.02506129 0.067479328
## SPL_EJI -0.555457278 0.88000177 0.849611389
## RPL_EJI -0.547689410 0.87036491 0.807295449
## SPL_SER -0.649638463 0.70902113 0.791070127
## RPL_SER -0.628415850 0.69054688 0.751169965
## EPL_OZONE 0.346022636 -0.35942418 -0.473858394
## EPL_PM -0.158106525 0.10887183 0.150326074
## EPL_DSLPM -0.495368750 0.48284888 0.567114614
## EPL_TOTCR -0.490764337 0.49251270 0.567845450
## SPL_EBM_THEME1 -0.214421889 0.17655549 0.136835308
## RPL_EBM_DOM1 -0.198109371 0.15976316 0.117036765
## EPL_NPL NA NA NA
## EPL_TRI -0.102946278 0.26377191 0.201800660
## EPL_TSD -0.050348407 -0.03447111 0.008525186
## EPL_RMP -0.089834324 -0.18029840 -0.045985577
## EPL_COAL NA NA NA
## EPL_LEAD NA NA NA
## SPL_EBM_THEME2 -0.181237072 0.09729495 0.156432407
## RPL_EBM_DOM2 -0.185696943 0.12585324 0.168493146
## EPL_PARK 0.127818388 -0.19978320 -0.124698627
## EPL_HOUAGE 0.235221283 -0.18734856 -0.284204020
## EPL_WLKIND 0.010767548 0.16002810 0.065559058
## SPL_EBM_THEME3 0.191410960 -0.06716292 -0.186877204
## RPL_EBM_DOM3 0.176815432 -0.05369894 -0.178147537
## EPL_RAIL -0.208856459 0.26479914 0.245970998
## EPL_ROAD -0.065314222 0.04819320 0.053088312
## EPL_AIRPRT -0.056463046 0.04185933 0.040831163
## SPL_EBM_THEME4 -0.223343298 0.25708384 0.242488645
## RPL_EBM_DOM4 -0.220362948 0.25991180 0.240112578
## EPL_IMPWTR -0.627877351 0.49872494 0.562673191
## SPL_EBM_THEME5 -0.627877351 0.49872494 0.562673191
## RPL_EBM_DOM5 -0.627882597 0.49869467 0.562672374
## SPL_EBM -0.198325266 0.18759443 0.175795809
## RPL_EBM -0.224213981 0.23677726 0.209418399
## EPL_MINRTY -0.751935026 0.79242664 0.663503459
## SPL_SVM_DOM1 -0.751935026 0.79242664 0.663503459
## RPL_SVM_DOM1 -0.751935026 0.79242664 0.663503459
## EPL_POV200 -0.752684853 0.73677575 0.916779502
## EPL_NOHSDP -0.677927071 0.72633903 0.827531193
## EPL_UNEMP -0.423922951 0.37064772 0.490190160
## EPL_RENTER -0.583170663 0.51907834 0.736308499
## EPL_HOUBDN -0.745288684 0.60914409 0.757725732
## EPL_UNINSUR -0.465400069 0.35765933 0.462100276
## EPL_NOINT -0.449385504 0.53884017 0.652908644
## SPL_SVM_DOM2 -0.756833609 0.71278346 0.896217570
## RPL_SVM_DOM2 -0.759258261 0.71186314 0.876682414
## EPL_AGE65 0.834895999 -0.40582081 -0.719345184
## EPL_AGE17 -0.623898814 0.54707453 0.722444400
## EPL_DISABL 0.071074787 0.20241364 0.147858095
## EPL_LIMENG -0.537177974 0.47303440 0.574049704
## SPL_SVM_DOM3 -0.004924552 0.39468348 0.301850997
## RPL_SVM_DOM3 -0.021326326 0.40254601 0.316235630
## EPL_MOBILE -0.031605337 -0.07292779 -0.017140229
## EPL_GROUPQ -0.008909423 0.06696525 0.131724702
## SPL_SVM_DOM4 -0.023050749 0.02230699 0.105289385
## RPL_SVM_DOM4 -0.004425679 0.01123089 0.092614984
## SPL_SVM -0.651567603 0.72525739 0.852402843
## RPL_SVM -0.670453110 0.73525076 0.844583223
## F_BPHIGH 0.093319992 0.45806526 0.176590441
## F_ASTHMA -0.608793076 0.71412089 0.697578027
## F_CANCER 0.803831213 -0.40513775 -0.565557972
## F_MHLTH -0.576789846 0.59997202 0.861422527
## F_DIABETES -0.510378641 0.84772245 0.642907054
## F_HVM -0.357918936 0.84243681 0.721714566
## RPL_HVM -0.357918936 0.84243681 0.721714566
## E_OZONE 0.416170774 -0.35793360 -0.513409976
## E_PM -0.165418689 0.11923932 0.160222484
## E_DSLPM -0.463042650 0.46274456 0.562542702
## E_TOTCR -0.483951306 0.50267674 0.586378386
## E_NPL NA NA NA
## E_TRI -0.149267601 0.27910599 0.225229181
## E_TSD -0.050348407 -0.03447111 0.008525186
## E_RMP -0.070497106 -0.10216180 -0.033777127
## E_COAL NA NA NA
## E_LEAD NA NA NA
## E_PARK -0.132620969 0.19271883 0.125139932
## E_HOUAGE 0.231142187 -0.18013708 -0.273423242
## E_WLKIND -0.013963943 -0.16746113 -0.069085049
## E_RAIL -0.206910366 0.25841943 0.246098162
## E_ROAD -0.046204590 0.03181788 0.038189646
## E_AIRPRT -0.054624121 0.02526804 0.059351475
## E_IMPWTR -0.586332749 0.46270633 0.517379222
## EP_MINRTY -0.759139564 0.79543299 0.664455175
## EP_POV200 -0.664509597 0.71917673 0.909615572
## EP_NOHSDP -0.601555220 0.69024580 0.851600685
## EP_UNEMP -0.394789591 0.34132193 0.490498089
## EP_RENTER -0.655729134 0.57336454 0.818879607
## EP_HOUBDN -0.659821331 0.54426336 0.738927940
## EP_UNINSUR -0.443165741 0.32692874 0.444217078
## EP_NOINT -0.382530207 0.53106165 0.626157676
## EP_AGE65 0.822363244 -0.35304242 -0.678427601
## EP_AGE17 -0.556855196 0.52086690 0.672487756
## EP_DISABL 0.101579438 0.15963499 0.108821539
## EP_LIMENG -0.561798974 0.45489083 0.613874037
## EP_MOBILE -0.003295030 -0.09063821 -0.055098576
## EP_GROUPQ 0.161918017 -0.17251017 -0.062618455
## EP_BPHIGH 0.184458754 0.65181479 0.195370418
## EP_ASTHMA -0.489951624 0.73584837 0.790418165
## EP_CANCER 0.965149622 -0.40557947 -0.743933368
## EP_MHLTH -0.693827630 0.69797869 0.968134200
## EP_DIABETES -0.330158236 0.87471028 0.725279743
## EPL_BPHIGH 0.123182926 0.68101817 0.253046530
## EPL_ASTHMA -0.653359851 0.80913433 0.825928399
## EPL_CANCER 1.000000000 -0.47431933 -0.762823969
## EPL_DIABETES -0.474319333 1.00000000 0.734006867
## EPL_MHLTH -0.762823969 0.73400687 1.000000000#RPL_EJI
#EP_MINRTY
#EP_POV200 # estimate below 200% Poverty line
#EP_NONHSDP # No high school degree
#EP_RENTER # estimate of renters
#EP_HOUBDN # households that make less than 75,000
#ELP_NOINT # Percentile rank of persons with no internet
#EP_ASTHMA # percentage with asthma
#F_CANCER # flag indicating tracts greater than 0.67 percentile rank with cancer
#EP_DIABETES # percentage of individuals with diabetes
#F_HVM # total number of tertile flags
#EP_MHLTH # percentage of individuals reporting not good mental health
eji_complex_bronx = eji_base_bronx[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200", "EP_NOHSDP", "EP_RENTER", "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER", "EP_DIABETES", "F_HVM", "EP_MHLTH")]
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_complex_bronx)), size = 231)
train = eji_complex_bronx[train_sample, ]
test = eji_complex_bronx[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 48.3%
kmeans_result ## K-means clustering with 2 clusters of sizes 155, 76
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 0.5270756 0.4366952 0.5737872 0.5315267 0.5193415 0.4784659 0.4626970
## 2 -1.0749568 -0.8906284 -1.1702239 -1.0840347 -1.0591834 -0.9758187 -0.9436584
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 0.4537587 -0.3237398 0.4528685 0.4660311 0.5497016
## 2 -0.9254289 0.6602589 -0.9236133 -0.9504582 -1.1211019
##
## Clustering vector:
## 42807 42638 42823 42935 42745 42928 42858 42873 42959 42780 42715 42716 42885
## 1 1 2 2 1 1 2 1 2 1 2 1 1
## 42825 42949 42764 42650 42631 42944 42883 42839 42703 42706 42667 42770 42656
## 1 2 1 1 1 1 1 2 1 1 1 1 1
## 42736 42892 42647 42762 42853 42793 42845 42919 42694 42697 42701 42688 42768
## 1 1 1 2 2 1 2 1 1 2 1 1 1
## 42838 42951 42906 42665 42950 42852 42640 42743 42719 42891 42864 42711 42663
## 2 2 1 1 2 1 1 1 2 1 2 2 1
## 42786 42869 42837 42658 42627 42637 42925 42872 42714 42649 42907 42748 42737
## 1 2 2 1 2 1 2 2 1 1 1 1 2
## 42785 42689 42827 42692 42778 42710 42792 42763 42675 42699 42806 42733 42865
## 1 2 2 1 2 1 2 1 1 2 2 1 2
## 42724 42948 42842 42754 42832 42840 42801 42641 42818 42670 42678 42790 42861
## 1 2 2 2 2 2 1 2 1 1 1 1 2
## 42895 42912 42704 42648 42740 42843 42734 42930 42849 42835 42890 42781 42729
## 1 1 1 1 1 2 1 1 2 2 1 1 1
## 42787 42918 42782 42797 42628 42695 42914 42882 42934 42645 42679 42700 42791
## 1 2 1 2 1 1 1 1 2 1 1 1 1
## 42708 42908 42871 42941 42932 42672 42702 42841 42812 42738 42876 42824 42624
## 1 1 2 1 1 1 2 2 2 1 1 1 2
## 42795 42654 42867 42848 42713 42939 42804 42644 42731 42718 42879 42676 42735
## 1 1 2 2 1 2 2 1 1 1 1 2 1
## 42646 42805 42666 42683 42709 42635 42896 42887 42900 42889 42933 42862 42859
## 1 1 2 1 1 1 1 1 1 1 1 1 2
## 42875 42799 42855 42660 42769 42947 42752 42657 42664 42634 42828 42633 42942
## 1 1 1 1 2 1 1 2 1 2 1 1 1
## 42854 42685 42779 42922 42958 42954 42943 42794 42742 42888 42677 42784 42822
## 1 2 1 1 1 2 1 1 1 1 1 1 2
## 42810 42898 42817 42929 42788 42916 42681 42732 42728 42931 42952 42868 42761
## 2 1 2 1 1 1 1 1 1 1 2 1 1
## 42946 42756 42940 42910 42937 42653 42772 42651 42884 42789 42684 42744 42808
## 2 2 1 2 1 1 2 1 1 1 1 1 2
## 42917 42811 42629 42741 42826 42655 42819 42874 42893 42661 42915 42821 42659
## 1 2 1 2 2 1 1 2 1 1 1 1 1
## 42899 42857 42691 42903 42880 42723 42851 42774 42632 42844
## 1 1 1 1 1 2 2 1 1 2
##
## Within cluster sum of squares by cluster:
## [1] 632.9354 794.6717
## (between_SS / total_SS = 48.3 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.45 <- worse than simplistic model## [1] 0.4533216fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 155 0.56
## 2 2 76 0.24
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 67% are in cluster 1 (higher ratings) <- minorities
# 33% are in cluster 2 (lower ratings) <- non-minorities
# higher across the board for everything except for the flag for cancer Testing Data
# Normalizing the data
z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 46.4%
kmeans_result ## K-means clustering with 2 clusters of sizes 26, 73
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 -1.3227434 -1.140454 -1.2982959 -1.1084992 -1.267572 -1.1984341 -0.7823517
## 2 0.4711141 0.406189 0.4624068 0.3948079 0.451464 0.4268395 0.2786458
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 -1.0272846 0.8093874 -1.1147601 -1.154450 -1.2532845
## 2 0.3658822 -0.2882750 0.3970378 0.411174 0.4463753
##
## Clustering vector:
## 42625 42626 42636 42639 42642 42643 42652 42662 42668 42669 42671 42673 42674
## 1 2 2 2 2 2 2 2 2 2 2 2 2
## 42680 42682 42687 42690 42693 42696 42698 42705 42707 42712 42717 42721 42722
## 2 2 2 2 2 2 2 2 2 2 1 1 2
## 42725 42727 42730 42739 42746 42747 42749 42750 42751 42753 42755 42757 42758
## 2 2 2 2 2 2 2 2 2 2 2 2 2
## 42759 42760 42765 42766 42767 42771 42773 42775 42776 42777 42783 42796 42798
## 2 2 2 2 2 2 1 2 2 2 1 2 2
## 42800 42802 42809 42813 42814 42815 42816 42820 42829 42830 42831 42833 42834
## 1 1 2 2 1 2 1 2 2 1 1 1 1
## 42836 42846 42847 42856 42860 42863 42866 42870 42877 42878 42881 42886 42894
## 1 1 1 2 2 2 1 1 1 2 2 2 2
## 42897 42901 42902 42904 42905 42909 42911 42913 42920 42921 42923 42924 42926
## 2 2 2 2 2 2 1 2 2 2 2 2 2
## 42927 42936 42938 42953 42955 42956 42957 42961
## 1 1 1 1 2 2 1 1
##
## Within cluster sum of squares by cluster:
## [1] 258.3896 371.9127
## (between_SS / total_SS = 46.4 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.45 <- worse than simplistic model## [1] 0.4541851fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 26 0.27
## 2 2 73 0.52
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 73% are in cluster 2 (higher ratings) <- minorities
# 27% are in cluster 1 (lower ratings) <- non-minorities
# higher across the board for everything except for the flag for cancer New York clustering analysis
Base Model
Training Data
eji_base_ny = eji_base[which(eji_base$COUNTY == 'New York'),]
eji_base_ny = na.omit(eji_base_ny)
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_base_ny)), size = 195)
train = eji_base_ny[train_sample, ]
test = eji_base_ny[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 78.7%
kmeans_result ## K-means clustering with 2 clusters of sizes 118, 77
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -0.722208 -0.6998813 -0.7233572
## 2 1.106760 1.0725453 1.1085215
##
## Clustering vector:
## 45097 44930 45113 45035 45148 45163 45200 45071 45007 45008 45176 45115 45190
## 1 1 2 2 2 2 1 1 2 1 2 2 2
## 45054 44942 44923 45186 45174 45129 44994 44997 44959 45061 44948 45153 45026
## 1 2 1 2 2 2 1 1 1 1 1 2 1
## 45184 45183 45087 44990 44939 45073 45106 44969 45052 45166 45168 45143 45084
## 1 1 2 1 2 1 1 1 1 2 2 2 1
## 45135 44950 45140 44985 44988 44992 44979 45059 45128 45014 45187 45192 44954
## 2 2 2 1 1 1 1 1 1 1 1 2 1
## 44937 45125 44957 45093 45191 44976 44932 45033 45011 44922 45118 45003 45134
## 2 2 1 2 2 1 2 1 2 1 1 1 2
## 44955 45077 45127 45197 44966 45158 44920 44929 45156 45044 45196 44968 44938
## 1 1 2 1 1 2 1 1 2 1 2 1 2
## 45006 45078 44941 44951 45086 45029 44946 45058 45131 45038 45027 45076 44980
## 1 1 2 1 1 1 1 1 2 1 1 1 1
## 45060 44983 45069 45039 44995 45002 45083 45053 44967 45170 45096 45023 45015
## 1 1 1 1 1 1 2 1 1 2 2 1 1
## 45201 45123 44933 44962 44970 45081 45109 45137 45102 44940 45030 45024 45165
## 1 1 2 1 1 1 2 2 1 1 1 1 2
## 45104 45072 45019 45088 45162 44921 44986 45157 45160 45189 45146 44971 44991
## 1 1 1 1 2 2 1 2 2 2 2 1 1
## 45000 45132 45089 45172 44964 44993 45067 45028 45066 44916 45198 45188 45108
## 1 2 2 2 1 1 1 2 1 2 2 2 1
## 45005 45065 44936 45021 45010 45121 45025 45120 44965 44958 44975 45001 44927
## 1 1 1 1 1 1 1 2 1 1 2 1 1
## 45110 45080 44924 45090 45101 45182 44982 45082 45062 45037 45074 45155 44960
## 2 1 2 1 2 2 1 1 1 2 1 2 1
## 45122 44952 44961 45193 45064 45004 44949 44956 45020 44926 45119 45114 44998
## 2 1 1 2 1 1 1 2 1 1 2 2 1
## 44925 45173 45013 44974 44977 45161 45079 45175 45111 45169 45185 45050 44973
## 2 2 1 1 1 2 1 2 2 2 2 2 1
##
## Within cluster sum of squares by cluster:
## [1] 59.70005 63.69456
## (between_SS / total_SS = 78.8 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.66 <- could potentially have a better algorithm## [1] 0.6641234fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 118 0.70
## 2 2 77 0.61
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 61% are in cluster 1 (lower ratings) <- non-minorities
# 39% are in cluster 2 (higher ratings) <- minorities
# same as the bronx
# lower E_PM but higher everything else
table(train$km.group, train$minority)##
## minority non-minority
## cl1 4 114
## cl2 74 3# cluster 1 has 5% of minority groups
# Are there significant differences?
aov_test = aov(RPL_EJI ~ km.group, data = train)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 7.231 7.231 593.2 <2e-16 ***
## Residuals 193 2.353 0.012
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(RPL_SVM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 16.29 16.29 801.8 <2e-16 ***
## Residuals 193 3.92 0.02
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(E_PM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 0.4046 0.4046 98.96 <2e-16 ***
## Residuals 193 0.7890 0.0041
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Testing Data
# Setting seed
set.seed(123)
z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 77.2%
kmeans_result ## K-means clustering with 2 clusters of sizes 47, 37
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -0.7781057 -0.7833481 -0.7635081
## 2 0.9884045 0.9950638 0.9698616
##
## Clustering vector:
## 44917 44919 44928 44931 44934 44935 44943 44944 44945 44947 44953 44963 44972
## 2 2 2 2 1 2 2 1 1 1 1 1 1
## 44978 44981 44984 44987 44989 44996 45009 45012 45016 45017 45018 45022 45031
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 45032 45034 45036 45040 45041 45042 45043 45045 45046 45047 45048 45049 45051
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 45055 45056 45063 45068 45070 45075 45085 45091 45092 45094 45095 45098 45099
## 1 1 1 1 1 2 2 2 1 1 2 1 2
## 45100 45103 45105 45107 45112 45116 45117 45124 45126 45130 45133 45136 45139
## 1 2 2 2 1 1 2 2 1 2 2 2 2
## 45141 45142 45144 45145 45147 45149 45150 45151 45152 45154 45159 45167 45171
## 2 1 2 2 2 2 2 2 2 2 2 2 2
## 45177 45178 45179 45180 45181 45195
## 2 2 1 2 2 2
##
## Within cluster sum of squares by cluster:
## [1] 40.38121 16.33761
## (between_SS / total_SS = 77.2 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.64 <- could potentially have a better algorithm## [1] 0.6397898fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 47 0.58
## 2 2 37 0.71
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 56% are in cluster 1 (higher ratings) <- non-minorities
# 44% are in cluster 2 (lower ratings) <- minorities
table(test$km.group, test$minority)##
## minority non-minority
## cl1 6 41
## cl2 36 1# cluster 1 has 14% of minority groups
# Are there significant differences?
aov_test = aov(RPL_EJI ~ km.group, data = test)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 3.357 3.357 306.4 <2e-16 ***
## Residuals 82 0.898 0.011
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(RPL_SVM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 6.556 6.556 245.2 <2e-16 ***
## Residuals 82 2.192 0.027
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(E_PM ~ km.group, data = test)
summary(aov_test) #yes there are significant differences## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 0.1971 0.19710 57.41 4.78e-11 ***
## Residuals 82 0.2815 0.00343
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1More Complex Model
Training Data
eji_base_ny = eji_ny[which(eji_ny$COUNTY == 'New York'),]
eji_base_ny = na.omit(eji_base_ny)
eji_complex_ny = eji_base_ny[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200", "EP_NOHSDP", "EP_RENTER", "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER", "EP_DIABETES", "F_HVM", "EP_MHLTH")]
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_complex_ny)), size = 231)
train = eji_complex_ny[train_sample, ]
test = eji_complex_ny[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 57%
kmeans_result ## K-means clustering with 2 clusters of sizes 84, 147
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 1.1393056 1.1567714 1.0987329 1.1077865 0.7677314 1.0667238 0.9755524
## 2 -0.6510318 -0.6610122 -0.6278474 -0.6330209 -0.4387037 -0.6095564 -0.5574585
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 1.0268780 -0.3304855 1.060019 0.8325441 1.0926050
## 2 -0.5867874 0.1888488 -0.605725 -0.4757395 -0.6243457
##
## Clustering vector:
## 45097 44930 45113 45035 45148 45163 45200 45071 45007 45008 45176 45115 45190
## 2 2 1 1 1 1 2 2 2 2 2 1 1
## 45054 44942 44923 45186 45174 45129 44994 44997 44959 45061 44948 45153 45026
## 2 1 2 1 1 1 2 2 2 2 2 1 2
## 45184 45183 45087 44990 44939 45073 45106 44969 45052 45166 45168 45143 45084
## 2 2 1 2 1 2 2 2 2 1 1 1 2
## 45135 44950 45140 44985 44988 44992 44979 45059 45128 45014 45187 45192 44954
## 1 1 1 2 2 2 2 2 2 2 2 1 2
## 44937 45125 44957 45093 45191 44976 44932 45033 45011 44922 45118 45003 45134
## 1 1 2 1 1 2 1 2 2 2 2 2 1
## 44955 45077 45127 45197 44966 45158 44920 44929 45156 45044 45196 44968 44938
## 2 2 1 2 2 1 2 2 1 2 1 2 1
## 45006 45078 44941 44951 45086 45029 44946 45058 45131 45038 45027 45076 44980
## 2 2 1 2 2 2 2 2 1 2 2 2 2
## 45060 44983 45069 45039 44995 45002 45083 45053 44967 45170 45096 45023 45015
## 2 2 2 2 2 2 1 2 2 1 1 2 2
## 45201 45123 44933 44962 44970 45081 45109 45137 45102 44940 45030 45024 45165
## 2 2 1 2 2 2 1 1 2 2 2 2 1
## 45104 45072 45019 45088 45162 44921 44986 45157 45160 45189 45146 44971 44991
## 2 2 2 2 2 1 2 1 1 1 1 2 2
## 45000 45132 45089 45172 44964 44993 45067 45028 45066 44916 45198 45188 45108
## 2 1 1 1 2 2 2 2 2 1 1 1 2
## 45005 45065 44936 45021 45010 45121 45025 45120 44965 44958 44975 45001 44927
## 2 2 2 2 2 2 2 1 2 2 1 2 2
## 45110 45080 44924 45090 45101 45182 44982 45082 45062 45037 45074 45155 44960
## 1 2 1 2 1 1 2 2 2 2 2 1 2
## 45122 44952 44961 45193 45064 45004 44949 44956 45020 44926 45119 45114 44998
## 1 2 2 1 2 2 2 1 2 2 1 1 2
## 44925 45173 45013 44974 44977 45161 45079 45175 45111 45169 45185 45050 44973
## 1 1 2 2 2 2 2 2 1 1 1 2 2
## 44945 45018 45195 45017 45032 45041 45117 45048 45022 45012 45180 45171 45149
## 1 2 1 2 2 2 1 2 2 2 1 1 1
## 45036 45099 45139 45136 45112 45055 45042 45154 44943 45070 45068 45141 45094
## 2 1 1 1 2 2 2 1 1 2 2 1 2
## 45107 45144 45051 44984 45151 45056 44947 44981 45091 44953
## 1 1 2 2 1 2 2 2 1 2
##
## Within cluster sum of squares by cluster:
## [1] 547.3105 638.7466
## (between_SS / total_SS = 57.0 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.49 <- worse than simplistic model## [1] 0.4924989fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 84 0.41
## 2 2 147 0.54
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 37% are in cluster 1 (higher ratings) <- minorities
# 63% are in cluster 2 (lower ratings) <- non-minorities
# higher across the board for everything except for the flag for cancer Testing Data
# Normalizing the data
z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 60.7%
kmeans_result ## K-means clustering with 2 clusters of sizes 27, 21
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 -0.7811379 -0.7499181 -0.7631320 -0.7183881 -0.5144063 -0.7006776 -0.7000508
## 2 1.0043202 0.9641804 0.9811697 0.9236419 0.6613796 0.9008712 0.9000653
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 -0.6225903 0.2320532 -0.7695131 -0.6972952 -0.7120020
## 2 0.8004733 -0.2983541 0.9893740 0.8965224 0.9154311
##
## Clustering vector:
## 44917 44919 44928 44931 44934 44935 44944 44963 44972 44978 44987 44989 44996
## 2 2 2 2 1 2 1 1 1 1 1 1 1
## 45009 45016 45031 45034 45040 45043 45045 45046 45047 45049 45063 45075 45085
## 1 1 1 1 1 1 1 1 1 1 1 2 2
## 45092 45095 45098 45100 45103 45105 45116 45124 45126 45130 45133 45142 45145
## 1 2 1 1 2 2 1 1 1 2 2 1 2
## 45147 45150 45152 45159 45167 45177 45178 45179 45181
## 2 2 2 2 2 2 2 1 2
##
## Within cluster sum of squares by cluster:
## [1] 141.04878 80.84272
## (between_SS / total_SS = 60.7 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.5 <- worse than simplistic model## [1] 0.4984769fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 27 0.47
## 2 2 21 0.53
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 56% are in cluster 1 (lower ratings) <- non-minorities
# 44% are in cluster 2 (higher ratings) <- minorities
# higher across the board for everything except for the flag for cancer Kings clustering analysis
Base Model
Training Data
eji_base_kings = eji_base[which(eji_base$COUNTY == 'Kings'),]
eji_base_kings = na.omit(eji_base_kings)
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_base_kings)), size = 524)
train = eji_base_kings[train_sample, ]
test = eji_base_kings[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 50%
kmeans_result ## K-means clustering with 2 clusters of sizes 224, 300
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -0.7965071 -0.829350 -0.8279588
## 2 0.5947253 0.619248 0.6182092
##
## Clustering vector:
## 44049 44097 43812 44160 43828 43749 43932 43862 43877 43643 44008 44304 44239
## 2 2 1 1 1 1 2 1 1 2 1 2 2
## 44240 44348 43721 43982 44287 43989 43655 44153 44060 44371 43844 44227 44230
## 2 2 1 1 2 2 1 1 2 2 2 2 1
## 44192 44007 43776 44179 44124 44259 43652 43942 43768 43857 43799 43850 43923
## 2 2 2 1 1 2 1 2 1 2 2 2 2
## 44218 43702 44225 44212 43774 43786 43927 43910 44387 43670 44065 43720 43949
## 2 2 2 2 2 1 1 2 1 1 2 1 2
## 43856 44162 43747 44243 44090 44235 43668 43792 43842 44378 43663 44150 43642
## 2 2 1 2 2 2 1 2 2 2 2 1 2
## 43699 44043 43941 43911 43719 44172 43924 44058 43919 44310 43752 43740 43791
## 2 2 1 2 1 1 1 2 2 2 1 1 1
## 43694 44117 44111 44114 43697 44302 43715 43798 44286 43680 43704 43811 43996
## 2 1 1 1 2 2 2 1 2 1 2 1 2
## 43869 44247 43963 43758 43845 43943 43876 43744 44257 44307 43784 44251 43793
## 2 2 1 1 2 2 1 1 2 2 2 2 2
## 44025 43788 44366 43633 43959 43913 44204 43871 43972 44329 43770 44089 44197
## 2 1 2 1 1 2 1 1 2 1 2 1 2
## 44226 43713 44273 43829 44314 44332 44134 43978 44290 44093 43649 44384 43797
## 2 1 2 2 1 2 2 2 2 1 1 2 2
## 43681 44168 43810 44191 43714 44157 44026 43935 44234 44269 44064 44062 43883
## 2 1 1 2 2 1 1 2 2 2 1 2 1
## 44063 44032 44334 44015 44180 43669 44156 44107 43833 43756 43898 43819 44210
## 2 1 2 2 1 1 1 1 2 1 2 2 2
## 43885 44092 43785 43683 44173 43868 43922 43818 44047 44236 44354 44246 43838
## 2 2 1 2 1 2 2 1 2 2 2 2 2
## 44317 44201 44282 44321 43980 44283 44102 44143 43686 44091 43991 43912 43903
## 1 1 2 2 2 2 1 2 1 2 2 2 2
## 43981 43761 43851 43970 44368 44174 44367 44190 44024 44132 43855 44055 44208
## 1 1 2 2 2 2 2 2 1 1 2 1 1
## 43796 44275 44324 44293 43858 44023 43748 44216 43684 44350 44388 43767 44081
## 2 2 1 2 2 1 1 1 1 2 1 2 2
## 43734 44362 43843 43983 44035 43891 44254 44020 44344 43653 44100 43763 44377
## 1 2 2 2 2 2 2 2 2 1 1 2 2
## 44011 43803 44079 43867 44056 44142 44309 43710 44308 44109 44316 43977 43956
## 2 2 2 2 1 1 2 2 2 1 1 2 2
## 44113 44084 43741 44205 44085 44027 43950 43928 44193 43920 44140 43703 43925
## 1 2 1 1 1 1 2 2 2 1 1 2 2
## 43859 44319 44012 43805 43930 44372 43723 44233 44382 44267 43870 44375 43737
## 2 2 1 1 2 2 1 1 2 2 2 2 1
## 43662 44268 44030 43988 44341 44327 43706 43724 44151 43659 44358 44068 43808
## 1 2 1 1 2 1 2 1 2 1 2 2 1
## 44326 44149 43746 44161 43971 43726 44099 43992 44385 44315 44280 44104 44199
## 1 1 1 1 1 1 1 2 2 2 2 1 1
## 44031 44038 43863 43781 43984 44059 44249 44057 43835 43711 44176 44105 43865
## 1 1 2 1 1 2 2 1 2 1 1 1 2
## 44289 43736 44009 43640 44288 43998 44167 44037 44166 43660 44048 44330 44263
## 2 1 2 2 2 2 1 2 1 1 1 2 2
## 44115 44088 43645 43830 44054 44297 44051 44046 44255 43641 44242 43696 43679
## 1 2 1 2 1 2 1 2 2 1 2 2 1
## 43837 44110 44360 44177 44018 43753 44033 44076 43948 43892 43987 43881 44223
## 2 1 2 1 1 1 1 1 2 2 2 2 2
## 43677 43964 43730 43738 43934 43638 44101 44277 44130 44270 44178 44272 44219
## 1 2 1 1 2 1 1 2 1 2 1 2 2
## 44029 44041 43636 43745 43894 43658 43939 44278 44298 43915 44137 43900 44086
## 1 2 1 1 2 1 2 2 2 2 1 2 1
## 43895 44352 44271 44364 43852 43817 43986 44281 43750 44262 44305 44311 44066
## 1 2 2 2 2 1 2 2 1 2 2 2 2
## 43665 44238 43873 43751 44228 43937 44039 44343 44042 43735 43914 43813 44071
## 1 2 2 1 1 2 1 2 2 1 2 1 1
## 43874 44165 43800 43676 43824 43666 43807 44374 43936 43840 43648 44294 44328
## 2 1 2 1 1 1 2 2 2 2 1 2 1
## 44221 43733 44380 44044 43821 43772 44127 44313 43822 43944 44200 44252 43667
## 2 1 2 2 1 1 2 2 2 1 2 2 1
## 44284 43952 44133 44195 44163 44002 44203 43650 43832 43717 44347 44034 44069
## 2 2 1 2 1 2 1 1 2 2 2 1 1
## 44357 44087 44004 44006 44188 43634 43759 43789 43921 43678 43860 43872 43826
## 2 1 1 1 1 1 1 1 2 2 1 2 2
## 44067 44001 44260 43823 43743 44119 44010 44072 43999 44274 43688 43690 44120
## 2 2 2 2 1 1 1 2 2 2 2 2 1
## 44136 44355 44131 43718 43765 44231 43884 43836 43879 43918 44338 44139 43976
## 2 2 2 1 1 2 2 2 2 2 2 1 2
## 43764 44122 43795 44155 43801 43708 44078 43957 43725 43854 44013 43794 44342
## 2 1 2 1 1 2 2 1 1 2 2 2 2
## 43875 43814 44206 44381 44017 43820 43804 43926 44215 43769 43709 43888 44022
## 2 2 1 2 2 2 2 1 1 1 1 2 2
## 44365 44125 44152 44126 43902 44351 43886 44073 43657 43880 44171 44108 43899
## 2 1 1 2 2 2 1 2 1 2 1 1 2
## 43732 43771 43739 44198 44339 44170 44202 44154 44383 43827 43908 43773 43878
## 1 1 1 2 2 1 1 1 2 2 1 1 2
## 43955 44292 44103 44096
## 1 2 1 2
##
## Within cluster sum of squares by cluster:
## [1] 401.1490 382.3079
## (between_SS / total_SS = 50.1 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
library(cluster)
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.42 <- could potentially have a better algorithm## [1] 0.4229785fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 224 0.36
## 2 2 300 0.47
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 43% are in cluster 1 (lower ratings) <- non-minorities
# 57% are in cluster 2 (higher ratings) <- minorities
table(train$km.group, train$minority)##
## minority non-minority
## cl1 31 193
## cl2 246 54# cluster 1 has 11% of minority groups
# Are there significant differences?
aov_test = aov(RPL_EJI ~ km.group, data = train)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 9.877 9.877 553.3 <2e-16 ***
## Residuals 522 9.318 0.018
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(RPL_SVM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences ## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 14.98 14.976 549.5 <2e-16 ***
## Residuals 522 14.23 0.027
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1aov_test = aov(E_PM ~ km.group, data = train)
summary(aov_test) #yes there are significant differences## Df Sum Sq Mean Sq F value Pr(>F)
## km.group 1 0.067 0.06688 4.637 0.0317 *
## Residuals 522 7.529 0.01442
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Testing Data
# Setting seed
set.seed(123)
z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 51.8%
kmeans_result ## K-means clustering with 2 clusters of sizes 79, 145
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -0.8911325 -1.0042743 -1.0186662
## 2 0.4855136 0.5471564 0.5549974
##
## Clustering vector:
## 43629 43630 43631 43632 43635 43637 43644 43646 43647 43651 43654 43656 43661
## 1 2 1 1 1 1 2 1 1 1 1 1 1
## 43664 43671 43672 43673 43674 43675 43682 43685 43687 43689 43691 43693 43695
## 1 1 1 1 1 1 2 2 2 2 2 2 2
## 43698 43700 43701 43705 43707 43712 43716 43722 43727 43728 43729 43731 43754
## 2 2 2 2 2 2 2 2 1 1 1 1 1
## 43755 43757 43766 43775 43777 43778 43779 43780 43782 43783 43787 43790 43802
## 1 1 1 1 2 2 1 2 1 1 1 1 2
## 43806 43809 43815 43816 43825 43831 43834 43839 43841 43846 43847 43848 43849
## 2 2 1 2 2 2 2 2 2 2 2 2 2
## 43853 43861 43864 43866 43882 43887 43889 43890 43893 43896 43897 43901 43904
## 2 2 2 2 2 2 1 2 2 1 2 2 2
## 43905 43906 43907 43909 43916 43917 43929 43931 43933 43938 43940 43945 43946
## 2 2 1 1 2 2 2 2 2 2 2 2 2
## 43947 43951 43953 43954 43958 43960 43961 43962 43965 43966 43967 43968 43969
## 2 2 2 2 2 2 1 2 2 2 2 2 2
## 43973 43975 43979 43985 43990 43993 43994 43995 43997 44000 44003 44005 44014
## 2 1 1 2 2 2 2 2 2 2 2 2 2
## 44016 44019 44021 44028 44036 44040 44045 44050 44052 44053 44061 44070 44074
## 1 1 1 1 2 2 2 1 1 1 2 2 1
## 44075 44077 44080 44082 44083 44094 44095 44098 44106 44112 44116 44118 44121
## 2 1 2 1 2 1 1 2 1 1 1 1 2
## 44123 44128 44129 44135 44138 44141 44144 44145 44146 44147 44148 44158 44159
## 1 2 1 1 2 1 2 1 2 2 1 1 1
## 44164 44175 44181 44182 44183 44184 44185 44189 44194 44196 44207 44209 44211
## 1 2 1 1 1 1 1 2 2 1 1 1 2
## 44213 44214 44217 44220 44222 44224 44229 44232 44237 44241 44244 44245 44248
## 2 2 2 2 2 2 1 2 2 2 2 2 2
## 44250 44256 44258 44261 44264 44265 44266 44276 44279 44285 44291 44295 44296
## 2 2 2 2 2 2 2 2 2 2 2 2 2
## 44299 44300 44303 44306 44312 44318 44320 44322 44323 44325 44331 44333 44335
## 2 2 1 2 1 1 1 2 2 1 2 2 2
## 44336 44337 44340 44345 44346 44349 44353 44356 44359 44361 44363 44370 44373
## 2 2 2 2 2 2 2 2 2 2 2 2 2
## 44376 44379 44386
## 2 2 1
##
## Within cluster sum of squares by cluster:
## [1] 122.9257 199.4323
## (between_SS / total_SS = 51.8 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.44 <- could potentially have a better algorithm## [1] 0.4433248fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 79 0.41
## 2 2 145 0.46
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 35% are in cluster 1 (higher ratings) <- non-minorities
# 65% are in cluster 2 (lower ratings) <- minorities
table(test$km.group, test$minority)##
## minority non-minority
## cl1 10 69
## cl2 119 26# cluster 1 has 7% of minority groupsMore Complex Model
Training Data
eji_base_kings = eji_ny[which(eji_ny$COUNTY == 'Kings'),]
eji_base_kings = na.omit(eji_base_kings)
eji_complex_kings = eji_base_kings[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200", "EP_NOHSDP", "EP_RENTER", "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER", "EP_DIABETES", "F_HVM", "EP_MHLTH")]
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_complex_kings)), size = 524)
train = eji_complex_kings[train_sample, ]
test = eji_complex_kings[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 36.9%
kmeans_result ## K-means clustering with 2 clusters of sizes 286, 238
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 -0.6891221 -0.4011102 -0.6470383 -0.4705562 -0.4657448 -0.5984083 -0.5842828
## 2 0.8281047 0.4820064 0.7775335 0.5654583 0.5596765 0.7190956 0.7021214
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 -0.5728664 0.1511191 -0.5932903 -0.6110597 -0.6429193
## 2 0.6884025 -0.1815968 0.7129455 0.7342987 0.7725837
##
## Clustering vector:
## 44049 44097 43812 44160 43828 43749 43932 43862 43877 43643 44008 44304 44239
## 1 1 1 1 1 1 2 1 1 2 1 1 2
## 44240 44348 43721 43982 44287 43989 43655 44153 44060 44371 43844 44227 44230
## 2 2 1 1 2 2 1 1 2 1 1 2 1
## 44192 44007 43776 44179 44124 44259 43652 43942 43768 43857 43799 43850 43923
## 1 2 2 1 1 2 1 2 1 2 2 1 2
## 44218 43702 44225 44212 43774 43786 43927 43910 44387 43670 44065 43720 43949
## 1 2 2 2 1 1 1 2 1 1 2 1 2
## 43856 44162 43747 44243 44090 44235 43668 43792 43842 44378 43663 44150 43642
## 2 1 1 2 2 2 1 1 1 2 2 1 2
## 43699 44043 43941 43911 43719 44172 43924 44058 43919 44310 43752 43740 43791
## 2 1 1 2 1 1 1 2 2 1 1 1 1
## 43694 44117 44111 44114 43697 44302 43715 43798 44286 43680 43704 43811 43996
## 2 1 1 1 2 1 1 1 2 1 2 2 1
## 43869 44247 43963 43758 43845 43943 43876 43744 44257 44307 43784 44251 43793
## 1 2 1 1 2 2 1 1 2 2 1 1 2
## 44025 43788 44366 43633 43959 43913 44204 43871 43972 44329 43770 44089 44197
## 1 1 2 1 1 2 1 1 2 1 2 2 1
## 44226 43713 44273 43829 44314 44332 44134 43978 44290 44093 43649 44384 43797
## 1 1 2 2 1 2 1 2 1 1 1 2 2
## 43681 44168 43810 44191 43714 44157 44026 43935 44234 44269 44064 44062 43883
## 2 1 1 1 2 1 1 1 2 2 2 2 1
## 44063 44032 44334 44015 44180 43669 44156 44107 43833 43756 43898 43819 44210
## 2 2 2 2 1 1 1 1 2 1 2 2 1
## 43885 44092 43785 43683 44173 43868 43922 43818 44047 44236 44354 44246 43838
## 2 2 1 2 1 2 2 2 1 2 2 2 2
## 44317 44201 44282 44321 43980 44283 44102 44143 43686 44091 43991 43912 43903
## 1 1 2 1 2 2 1 1 1 1 1 2 2
## 43981 43761 43851 43970 44368 44174 44367 44190 44024 44132 43855 44055 44208
## 2 1 2 2 2 1 2 1 1 1 1 1 1
## 43796 44275 44324 44293 43858 44023 43748 44216 43684 44350 44388 43767 44081
## 2 2 1 2 1 1 1 1 1 1 1 1 2
## 43734 44362 43843 43983 44035 43891 44254 44020 44344 43653 44100 43763 44377
## 1 2 2 2 2 2 2 2 2 1 1 1 2
## 44011 43803 44079 43867 44056 44142 44309 43710 44308 44109 44316 43977 43956
## 1 2 2 2 1 1 1 2 2 1 1 1 1
## 44113 44084 43741 44205 44085 44027 43950 43928 44193 43920 44140 43703 43925
## 1 2 1 1 2 2 2 2 1 1 1 2 2
## 43859 44319 44012 43805 43930 44372 43723 44233 44382 44267 43870 44375 43737
## 2 1 1 2 2 2 1 1 2 2 2 2 1
## 43662 44268 44030 43988 44341 44327 43706 43724 44151 43659 44358 44068 43808
## 1 2 2 1 2 1 2 1 1 1 2 2 1
## 44326 44149 43746 44161 43971 43726 44099 43992 44385 44315 44280 44104 44199
## 1 1 1 1 1 1 1 1 2 1 2 1 1
## 44031 44038 43863 43781 43984 44059 44249 44057 43835 43711 44176 44105 43865
## 2 2 2 1 2 2 2 1 2 1 1 1 2
## 44289 43736 44009 43640 44288 43998 44167 44037 44166 43660 44048 44330 44263
## 2 1 2 2 2 2 1 2 1 1 1 2 2
## 44115 44088 43645 43830 44054 44297 44051 44046 44255 43641 44242 43696 43679
## 1 2 1 2 1 1 1 2 2 1 2 2 1
## 43837 44110 44360 44177 44018 43753 44033 44076 43948 43892 43987 43881 44223
## 2 1 2 1 1 1 1 1 2 2 2 2 2
## 43677 43964 43730 43738 43934 43638 44101 44277 44130 44270 44178 44272 44219
## 1 2 1 1 2 1 1 2 1 2 1 2 2
## 44029 44041 43636 43745 43894 43658 43939 44278 44298 43915 44137 43900 44086
## 2 1 1 1 1 1 2 2 1 2 1 2 1
## 43895 44352 44271 44364 43852 43817 43986 44281 43750 44262 44305 44311 44066
## 1 2 2 1 1 2 2 2 1 2 1 2 2
## 43665 44238 43873 43751 44228 43937 44039 44343 44042 43735 43914 43813 44071
## 1 1 1 1 1 2 1 2 2 1 2 2 1
## 43874 44165 43800 43676 43824 43666 43807 44374 43936 43840 43648 44294 44328
## 2 1 1 1 1 1 2 2 2 1 1 1 1
## 44221 43733 44380 44044 43821 43772 44127 44313 43822 43944 44200 44252 43667
## 2 1 2 2 2 1 1 1 2 1 1 2 1
## 44284 43952 44133 44195 44163 44002 44203 43650 43832 43717 44347 44034 44069
## 2 1 1 1 1 1 1 1 2 2 1 2 1
## 44357 44087 44004 44006 44188 43634 43759 43789 43921 43678 43860 43872 43826
## 2 2 1 1 1 1 1 1 2 2 1 1 2
## 44067 44001 44260 43823 43743 44119 44010 44072 43999 44274 43688 43690 44120
## 2 2 2 2 1 1 1 2 2 2 1 2 1
## 44136 44355 44131 43718 43765 44231 43884 43836 43879 43918 44338 44139 43976
## 1 2 1 1 1 2 2 1 1 2 2 1 2
## 43764 44122 43795 44155 43801 43708 44078 43957 43725 43854 44013 43794 44342
## 2 1 2 1 2 2 1 1 1 1 2 1 2
## 43875 43814 44206 44381 44017 43820 43804 43926 44215 43769 43709 43888 44022
## 2 2 1 2 2 2 2 1 1 1 1 2 2
## 44365 44125 44152 44126 43902 44351 43886 44073 43657 43880 44171 44108 43899
## 1 1 1 1 2 2 1 2 1 2 1 1 2
## 43732 43771 43739 44198 44339 44170 44202 44154 44383 43827 43908 43773 43878
## 1 1 1 2 2 1 1 1 2 1 1 1 1
## 43955 44292 44103 44096
## 1 1 1 2
##
## Within cluster sum of squares by cluster:
## [1] 2038.849 1918.665
## (between_SS / total_SS = 36.9 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.3 <- worse than simplistic model## [1] 0.3032509fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 286 0.32
## 2 2 238 0.28
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 54% are in cluster 1 (higher ratings) <- non-minorities
# 46% are in cluster 2 (lower ratings) <- minorities
# higher across the board for everything (even cancer flag)Testing Data
# Normalizing the data
z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 37.9%
kmeans_result ## K-means clustering with 2 clusters of sizes 114, 110
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 -0.7567783 -0.4538955 -0.7027089 -0.5087535 -0.5092228 -0.6918298 -0.6260091
## 2 0.7842975 0.4704007 0.7282620 0.5272536 0.5277400 0.7169872 0.6487731
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 -0.5982866 0.1786780 -0.6670296 -0.6043358 -0.7095166
## 2 0.6200424 -0.1851754 0.6912852 0.6263116 0.7353172
##
## Clustering vector:
## 43629 43630 43631 43632 43635 43637 43644 43646 43647 43651 43654 43656 43661
## 1 2 1 1 1 1 2 1 1 1 1 1 1
## 43664 43671 43672 43673 43674 43675 43682 43685 43687 43689 43691 43693 43695
## 1 1 1 1 1 1 2 2 2 2 2 1 2
## 43698 43700 43701 43705 43707 43712 43716 43722 43727 43728 43729 43731 43754
## 2 1 2 2 2 2 2 2 1 1 1 1 1
## 43755 43757 43766 43775 43777 43778 43779 43780 43782 43783 43787 43790 43802
## 1 1 1 1 2 2 1 2 1 1 1 1 1
## 43806 43809 43815 43816 43825 43831 43834 43839 43841 43846 43847 43848 43849
## 2 2 2 2 2 1 2 2 2 2 1 2 1
## 43853 43861 43864 43866 43882 43887 43889 43890 43893 43896 43897 43901 43904
## 2 2 1 2 2 1 1 2 1 1 2 2 2
## 43905 43906 43907 43909 43916 43917 43929 43931 43933 43938 43940 43945 43946
## 2 2 2 1 2 2 2 2 2 2 2 2 2
## 43947 43951 43953 43954 43958 43960 43961 43962 43965 43966 43967 43968 43969
## 2 2 1 2 2 1 1 2 1 2 1 2 2
## 43973 43975 43979 43985 43990 43993 43994 43995 43997 44000 44003 44005 44014
## 2 1 1 2 1 1 1 2 2 1 1 2 1
## 44016 44019 44021 44028 44036 44040 44045 44050 44052 44053 44061 44070 44074
## 1 1 1 2 1 2 1 1 1 1 2 2 1
## 44075 44077 44080 44082 44083 44094 44095 44098 44106 44112 44116 44118 44121
## 1 1 1 1 2 1 1 2 1 1 1 1 2
## 44123 44128 44129 44135 44138 44141 44144 44145 44146 44147 44148 44158 44159
## 1 1 1 1 1 1 1 1 2 2 1 1 1
## 44164 44175 44181 44182 44183 44184 44185 44189 44194 44196 44207 44209 44211
## 1 1 1 1 1 1 1 1 1 1 1 1 2
## 44213 44214 44217 44220 44222 44224 44229 44232 44237 44241 44244 44245 44248
## 2 2 1 1 2 2 1 2 2 2 2 2 1
## 44250 44256 44258 44261 44264 44265 44266 44276 44279 44285 44291 44295 44296
## 2 2 2 2 2 2 2 2 2 2 2 2 1
## 44299 44300 44303 44306 44312 44318 44320 44322 44323 44325 44331 44333 44335
## 2 1 1 1 1 1 1 1 1 1 2 2 2
## 44336 44337 44340 44345 44346 44349 44353 44356 44359 44361 44363 44370 44373
## 2 2 2 2 2 2 2 2 2 2 2 1 1
## 44376 44379 44386
## 2 2 2
##
## Within cluster sum of squares by cluster:
## [1] 810.0261 852.7461
## (between_SS / total_SS = 37.9 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.3 <- worse than simplistic model## [1] 0.302411fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 114 0.31
## 2 2 110 0.29
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 51% are in cluster 1 (lower ratings) <- non-minorities
# 49% are in cluster 2 (higher ratings) <- minorities
# higher across the board for everything except for the flag for cancer Queens clustering analysis
Base Model
Training Data
eji_base_queens = eji_base[which(eji_base$COUNTY == 'Queens'),]
eji_base_queens = na.omit(eji_base_queens)
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_base_queens)), size = 449)
train = eji_base_queens[train_sample, ]
test = eji_base_queens[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 50.5%
kmeans_result ## K-means clustering with 2 clusters of sizes 195, 254
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -0.8155717 -0.8446015 -0.7692942
## 2 0.6261279 0.6484146 0.5905999
##
## Clustering vector:
## 46087 46138 45843 46204 45859 45778 45968 45895 45910 45670 46043 46284 46285
## 1 1 2 1 2 2 2 2 2 2 1 1 1
## 45751 46017 46024 45683 46197 46100 45875 46271 46274 46234 46042 45804 46222
## 2 2 2 2 2 1 2 1 2 2 2 2 2
## 46166 45679 45978 45796 45890 45829 45882 45959 46261 45731 46268 46255 45802
## 1 2 2 1 2 2 2 2 2 2 2 2 1
## 45814 45963 45946 46323 45699 46105 45750 45985 45888 46206 45776 46131 45697
## 2 2 1 1 1 1 2 2 2 2 2 1 1
## 45820 45873 46314 45692 46194 45669 45728 46081 45977 45947 45749 46215 45960
## 1 2 1 2 1 1 1 2 2 2 1 1 2
## 46098 45955 45781 45770 45819 45722 46158 46152 46155 45726 45745 45828 45709
## 1 2 2 2 2 1 2 1 1 1 1 2 1
## 45734 45842 46031 45902 45999 45787 45876 45979 45909 45773 46249 45812 45822
## 2 2 2 2 2 2 1 2 2 2 1 2 1
## 46060 45816 46306 45661 45995 45949 45904 46008 46304 45798 46130 45743 46220
## 1 2 2 1 1 2 2 1 1 1 1 1 1
## 45860 46286 46176 46013 46235 46134 45676 46320 45827 45710 45841 45744 46201
## 2 1 2 2 1 1 2 1 2 1 2 2 1
## 46061 45971 46104 46102 45918 46103 46069 46050 45698 46148 45864 45785 46177
## 1 2 2 1 2 1 2 1 1 1 1 2 2
## 45934 45931 46229 45850 45719 45920 46133 45813 45988 45712 46079 46308 45901
## 2 2 1 2 2 2 1 2 2 1 2 1 2
## 45958 45849 45921 46085 45775 45666 46296 46178 45869 46032 45936 45682 46303
## 2 2 1 1 1 1 1 2 2 2 2 2 1
## 45951 46185 46262 45880 46015 46230 46143 46080 45715 46132 45765 46026 45948
## 2 2 2 2 2 2 1 2 1 1 2 2 2
## 45939 46035 45795 46016 45790 45883 45766 46038 46184 46006 45954 46213 45684
## 2 2 1 1 2 1 1 1 2 1 2 1 2
## 45663 46118 45911 45815 46279 46236 46059 45887 46269 46018 45806 46122 46094
## 2 1 2 2 1 1 1 2 2 2 1 1 1
## 46232 45809 45826 46299 45823 45725 45660 46239 45891 46058 45777 46163 45797
## 1 2 2 1 1 2 2 1 2 1 1 2 2
## 45713 46291 46246 45703 45807 45834 46324 46145 45863 46030 45840 46072 46151
## 2 2 1 1 2 2 2 1 2 1 2 1 1
## 46168 45764 46093 46179 46099 45874 46124 46095 46112 45926 46205 46055 46312
## 2 1 2 2 1 2 1 2 2 2 1 2 1
## 45680 45791 46245 45855 45736 46046 45938 46199 45862 46241 45900 46037 46251
## 2 2 1 2 2 1 2 1 2 2 2 1 2
## 45740 45694 46257 46172 46012 45992 45706 45771 46193 45986 45964 46126 45956
## 2 1 2 2 2 1 1 1 2 2 2 1 2
## 46052 45733 45961 45892 46260 45836 45966 46310 45753 46189 46318 46216 45903
## 1 2 2 2 2 2 2 1 1 2 1 2 2
## 46076 45767 45690 46217 46023 46282 46287 46074 45754 46202 45687 46106 45839
## 1 1 2 1 2 1 1 1 2 1 2 1 2
## 46111 46170 46007 45756 46071 46021 46136 45896 46119 45866 45741 46022 45898
## 2 1 2 1 2 1 1 2 1 2 1 2 2
## 46302 46141 45667 46233 46153 45688 46033 46073 46029 46156 45672 45861 46242
## 2 2 2 1 1 2 1 1 2 1 2 2 1
## 46082 45668 46115 45708 45868 46025 46227 45782 45984 45927 45916 46174 46057
## 1 1 2 1 2 2 2 2 1 2 2 2 1
## 45760 45768 45970 46169 46020 46224 46196 46219 45990 45664 45774 45929 45686
## 1 2 2 2 2 1 1 1 1 2 2 2 2
## 46243 46161 46049 46164 45930 46294 45994 46305 45884 45848 46228 45779 46247
## 1 2 2 2 2 1 2 1 2 2 1 2 1
## 46253 46309 46063 46107 45906 45780 45982 46313 46276 46150 45844 46004 45907
## 2 1 1 1 2 1 1 1 1 1 2 2 2
## 46188 45830 45705 46075 45695 45838 46167 45871 45675 46190 46125 45942 45763
## 1 2 1 1 2 2 2 2 2 1 1 2 2
## 46316 46054 45852 45800 46252 45853 45989 46120 45786 45696 46321 45721 45941
## 1 1 2 2 2 2 2 1 1 1 1 2 2
## 45738 45729 46307 46078 46137 45937 45735 45677 46173 46088 45747 46288 45717
## 2 2 1 1 1 2 1 2 2 2 1 1 1
## 46002 46066 46014 46051 45987 45831 45662 45789 46056 45817 45689 45707 45885
## 2 1 2 1 1 1 2 2 1 2 1 1 2
## 45922 45857 46000 45867 45944 46144 46089 45854 45772 45943 46142 46048 46005
## 2 2 1 2 2 1 1 2 2 2 2 1 1
## 45953 45877 45905 45893 46295 46183 46292 46289 45957 46110 46297 45965 45825
## 2 1 2 2 1 2 1 1 2 2 1 2 1
## 45748 45793 45846 45818 46139 46283 46322
## 2 2 2 2 1 1 1
##
## Within cluster sum of squares by cluster:
## [1] 367.9419 296.8786
## (between_SS / total_SS = 50.5 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
library(cluster)
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.43 <- could potentially have a better algorithm## [1] 0.4277348fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 195 0.34
## 2 2 254 0.49
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 43% are in cluster 1 (lower ratings) <- non-minorities
# 57% are in cluster 2 (higher ratings) <- minorities
table(train$km.group, train$minority)##
## minority non-minority
## cl1 35 160
## cl2 230 24# cluster 1 has 13% of minority groupsTesting Data
# Setting seed
set.seed(123)
z = test[, c(5:7)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 2 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 2) # default gives 49%
kmeans_result ## K-means clustering with 2 clusters of sizes 81, 111
##
## Cluster means:
## EP_MINRTY RPL_EJI RPL_SVM
## 1 -0.6860400 -0.8714353 -0.8799832
## 2 0.5006238 0.6359122 0.6421499
##
## Clustering vector:
## 45657 45658 45659 45665 45671 45673 45674 45678 45685 45693 45700 45701 45702
## 1 2 2 2 2 2 2 1 2 2 1 1 2
## 45704 45711 45714 45716 45718 45720 45723 45727 45730 45737 45739 45742 45746
## 1 2 2 2 1 1 2 2 1 1 1 2 2
## 45752 45755 45757 45758 45759 45761 45762 45769 45783 45784 45792 45794 45799
## 2 2 1 1 2 2 2 1 2 2 2 2 2
## 45801 45803 45805 45808 45810 45811 45832 45835 45837 45845 45847 45851 45856
## 1 2 2 2 2 2 2 2 1 2 2 2 2
## 45858 45865 45870 45872 45879 45881 45886 45894 45897 45899 45908 45912 45915
## 1 2 2 2 2 2 1 2 2 2 2 2 2
## 45917 45919 45923 45924 45925 45928 45933 45935 45940 45945 45950 45952 45962
## 1 1 2 2 2 2 2 1 2 2 2 1 2
## 45967 45969 45972 45973 45974 45975 45976 45980 45981 45983 45991 45993 45996
## 2 1 2 2 2 2 1 2 2 1 2 2 2
## 45997 45998 46001 46003 46009 46010 46011 46019 46027 46028 46034 46036 46039
## 1 1 2 1 1 1 2 2 2 1 1 2 2
## 46040 46041 46044 46045 46047 46053 46064 46065 46068 46070 46083 46084 46086
## 2 1 2 1 1 1 1 1 1 1 1 1 1
## 46090 46092 46097 46101 46108 46109 46113 46114 46116 46117 46121 46123 46127
## 1 1 1 2 1 1 2 1 2 2 1 1 1
## 46128 46135 46140 46146 46147 46149 46154 46157 46159 46162 46165 46171 46175
## 1 1 1 1 1 1 1 2 2 2 2 2 2
## 46180 46181 46182 46186 46187 46195 46198 46200 46203 46207 46208 46209 46210
## 2 2 2 1 2 2 1 2 2 2 2 2 2
## 46211 46212 46214 46218 46221 46225 46226 46231 46238 46240 46244 46248 46250
## 2 1 1 1 2 2 2 2 1 1 1 1 2
## 46254 46256 46258 46259 46263 46264 46265 46266 46267 46272 46273 46275 46277
## 2 2 1 2 2 1 2 2 2 1 1 1 2
## 46278 46280 46290 46298 46300 46301 46311 46315 46317 46319
## 1 1 1 1 1 1 1 1 2 1
##
## Within cluster sum of squares by cluster:
## [1] 175.0552 117.1092
## (between_SS / total_SS = 49.0 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.43 <- could potentially have a better algorithm## [1] 0.4297789# all of cluster 1 remains under the average and has some negative values
fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 81 0.30
## 2 2 111 0.53
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
E_PM = mean(E_PM),
RPL_EJI = mean(RPL_EJI),
RPL_SVM = mean(RPL_SVM))# 42% are in cluster 1 (higher ratings) <- non-minorities
# 58% are in cluster 2 (lower ratings) <- minorities
table(test$km.group, test$minority)##
## minority non-minority
## cl1 21 60
## cl2 95 16# cluster 1 has 18% of minority groupsMore Complex Model
Training Data
eji_base_queens = eji_ny[which(eji_ny$COUNTY == 'Queens'),]
eji_base_queens = na.omit(eji_base_queens)
eji_complex_queens = eji_base_queens[, c("NAME", "COUNTY", "RPL_EJI", "EP_MINRTY", "EP_POV200", "EP_NOHSDP", "EP_RENTER", "EP_HOUBDN", "EPL_NOINT", "EP_ASTHMA","F_CANCER", "EP_DIABETES", "F_HVM", "EP_MHLTH")]
# Setting seed
set.seed(123)
train_sample = sample(seq_len(nrow(eji_complex_queens)), size = 449)
train = eji_complex_queens[train_sample, ]
test = eji_complex_queens[-train_sample, ]
# Training data
# Normalizing the data
z = train[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# How many clusters?
fviz_nbclust(nor, kmeans, method = "silhouette") # 5 clusters
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 4) # default gives 56.5%
kmeans_result ## K-means clustering with 4 clusters of sizes 116, 83, 65, 185
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 0.9585426 0.6739372 1.2846043 1.0671806 0.7768907 1.10717406 0.8023883
## 2 0.3826889 0.9669762 -0.5676920 -0.2772783 -0.9475415 -0.47545063 -0.0217133
## 3 -1.3581753 -1.2130288 -1.0217715 -0.9873321 -0.9310985 -1.18957595 -0.6217621
## 4 -0.2955282 -0.4302101 -0.1917866 -0.1978501 0.2651244 -0.06295866 -0.2749205
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 0.1713256 -0.1799775 0.8820886 0.3750610 0.8564244
## 2 1.4249872 -0.3037293 0.7073637 1.3778081 0.4336809
## 3 -0.7881922 1.5182777 -0.7219856 -0.3270108 -1.3258806
## 4 -0.4698119 -0.2843304 -0.6167805 -0.7384294 -0.2657216
##
## Clustering vector:
## 46087 46138 45843 46204 45859 45778 45968 45895 45910 45670 46043 46284 46285
## 3 3 4 4 1 2 4 1 1 4 4 3 3
## 45751 46017 46024 45683 46197 46100 45875 46271 46274 46234 46042 45804 46222
## 1 2 1 1 4 3 2 4 1 4 2 4 1
## 46166 45679 45978 45796 45890 45829 45882 45959 46261 45731 46268 46255 45802
## 4 1 4 4 2 1 4 1 4 1 1 1 4
## 45814 45963 45946 46323 45699 46105 45750 45985 45888 46206 45776 46131 45697
## 1 1 4 3 4 3 4 4 2 4 4 4 4
## 45820 45873 46314 45692 46194 45669 45728 46081 45977 45947 45749 46215 45960
## 4 1 3 1 3 4 4 4 4 3 4 3 4
## 46098 45955 45781 45770 45819 45722 46158 46152 46155 45726 45745 45828 45709
## 4 1 4 2 1 4 2 4 4 4 4 1 4
## 45734 45842 46031 45902 45999 45787 45876 45979 45909 45773 46249 45812 45822
## 2 2 4 1 2 2 4 4 2 4 4 1 4
## 46060 45816 46306 45661 45995 45949 45904 46008 46304 45798 46130 45743 46220
## 4 1 3 3 4 1 1 2 4 4 4 4 3
## 45860 46286 46176 46013 46235 46134 45676 46320 45827 45710 45841 45744 46201
## 2 3 1 1 3 3 4 3 1 4 4 1 4
## 46061 45971 46104 46102 45918 46103 46069 46050 45698 46148 45864 45785 46177
## 2 1 2 3 1 3 2 4 4 3 2 2 1
## 45934 45931 46229 45850 45719 45920 46133 45813 45988 45712 46079 46308 45901
## 2 2 3 1 1 1 4 2 2 4 2 4 1
## 45958 45849 45921 46085 45775 45666 46296 46178 45869 46032 45936 45682 46303
## 4 4 2 3 4 4 3 1 1 4 1 4 4
## 45951 46185 46262 45880 46015 46230 46143 46080 45715 46132 45765 46026 45948
## 4 1 1 1 2 1 3 4 4 4 1 4 1
## 45939 46035 45795 46016 45790 45883 45766 46038 46184 46006 45954 46213 45684
## 2 1 4 4 2 4 4 4 1 4 1 4 4
## 45663 46118 45911 45815 46279 46236 46059 45887 46269 46018 45806 46122 46094
## 4 4 1 4 4 3 4 4 4 2 4 3 2
## 46232 45809 45826 46299 45823 45725 45660 46239 45891 46058 45777 46163 45797
## 4 2 4 4 4 2 4 3 2 2 4 1 2
## 45713 46291 46246 45703 45807 45834 46324 46145 45863 46030 45840 46072 46151
## 4 4 4 4 2 4 4 3 1 4 4 4 4
## 46168 45764 46093 46179 46099 45874 46124 46095 46112 45926 46205 46055 46312
## 2 4 2 1 3 4 3 2 2 1 4 2 3
## 45680 45791 46245 45855 45736 46046 45938 46199 45862 46241 45900 46037 46251
## 4 2 3 1 1 4 1 4 1 4 1 2 1
## 45740 45694 46257 46172 46012 45992 45706 45771 46193 45986 45964 46126 45956
## 4 4 4 1 2 4 4 4 1 1 1 3 1
## 46052 45733 45961 45892 46260 45836 45966 46310 45753 46189 46318 46216 45903
## 4 1 1 4 1 4 4 3 4 4 3 1 2
## 46076 45767 45690 46217 46023 46282 46287 46074 45754 46202 45687 46106 45839
## 4 4 1 3 4 3 3 4 4 4 1 4 1
## 46111 46170 46007 45756 46071 46021 46136 45896 46119 45866 45741 46022 45898
## 2 4 2 3 2 2 3 2 4 2 4 1 1
## 46302 46141 45667 46233 46153 45688 46033 46073 46029 46156 45672 45861 46242
## 4 4 4 4 3 1 4 2 4 1 1 1 3
## 46082 45668 46115 45708 45868 46025 46227 45782 45984 45927 45916 46174 46057
## 2 3 2 4 2 1 1 1 4 1 2 1 4
## 45760 45768 45970 46169 46020 46224 46196 46219 45990 45664 45774 45929 45686
## 4 1 2 1 4 4 3 3 4 4 1 1 1
## 46243 46161 46049 46164 45930 46294 45994 46305 45884 45848 46228 45779 46247
## 4 1 2 1 1 3 2 4 2 1 3 2 3
## 46253 46309 46063 46107 45906 45780 45982 46313 46276 46150 45844 46004 45907
## 1 3 2 3 2 4 4 3 4 3 1 2 1
## 46188 45830 45705 46075 45695 45838 46167 45871 45675 46190 46125 45942 45763
## 3 1 4 2 4 4 2 2 1 3 3 1 1
## 46316 46054 45852 45800 46252 45853 45989 46120 45786 45696 46321 45721 45941
## 3 4 4 2 1 1 2 4 4 4 3 4 1
## 45738 45729 46307 46078 46137 45937 45735 45677 46173 46088 45747 46288 45717
## 1 2 4 4 3 1 4 4 4 2 4 3 4
## 46002 46066 46014 46051 45987 45831 45662 45789 46056 45817 45689 45707 45885
## 2 4 2 2 2 4 4 2 2 2 3 4 4
## 45922 45857 46000 45867 45944 46144 46089 45854 45772 45943 46142 46048 46005
## 1 1 4 4 1 3 4 2 1 1 4 4 2
## 45953 45877 45905 45893 46295 46183 46292 46289 45957 46110 46297 45965 45825
## 4 4 2 1 3 1 4 4 1 1 4 1 4
## 45748 45793 45846 45818 46139 46283 46322
## 4 1 2 1 3 3 4
##
## Within cluster sum of squares by cluster:
## [1] 914.9091 336.2349 509.8658 841.5435
## (between_SS / total_SS = 51.6 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.24 <- worse than simplistic model## [1] 0.2616579fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 116 0.17
## 2 2 83 0.39
## 3 3 65 0.17
## 4 4 185 0.30
# Adding Clusters to data set
train = train %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2", "cl3", "cl4")))
# Summarizing the cluster groups
train %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 24% are in cluster 1 (minority
# 9% are in cluster 2 (minority) (always the highest except for cancer)
# 14% are in cluster 3 (non-minority) (usually always the lowest except for cancer)
# 34% are in cluster 4 (non-minority)
# 18% are in cluster 5 (minority)Testing Data
set.seed(123)
# Normalizing the data
z = test[, c(3:14)]
means = apply(z, 2, mean)
sds = apply(z, 2, sd)
nor = scale(z, center = means, scale = sds)
# K Means on 2 Clusters
kmeans_result = kmeans(nor, centers = 5) # default gives 58.8%
kmeans_result ## K-means clustering with 5 clusters of sizes 11, 46, 64, 17, 54
##
## Cluster means:
## RPL_EJI EP_MINRTY EP_POV200 EP_NOHSDP EP_RENTER EP_HOUBDN EPL_NOINT
## 1 -0.2574120 -1.8364588 -0.9960216 -0.7255288 -1.13149693 -1.2194227 0.1328327
## 2 0.3127388 0.9347425 -0.5150598 -0.2802437 -0.81919858 -0.4990581 -0.2143644
## 3 -0.8840681 -0.8373478 -0.5323650 -0.6602677 0.02537434 -0.3829706 -0.4649126
## 4 1.1258262 0.7804925 1.9174499 2.0349300 1.32350372 1.1891497 1.4758598
## 5 0.4793863 0.3245329 0.6689573 0.5284325 0.48159407 0.7530536 0.2419333
## EP_ASTHMA F_CANCER EP_DIABETES F_HVM EP_MHLTH
## 1 -0.3701351 4.045843 -0.3855915 0.5780900 -0.9403298
## 2 1.2485007 -0.245880 0.6793250 1.1703626 0.3798626
## 3 -0.6925170 -0.245880 -0.9097650 -0.8312405 -0.7183850
## 4 0.6376373 -0.245880 1.2254617 0.6397292 1.6314760
## 5 -0.3681165 -0.245880 0.1923086 -0.3309569 0.2057684
##
## Clustering vector:
## 45657 45658 45659 45665 45671 45673 45674 45678 45685 45693 45700 45701 45702
## 3 5 5 5 5 5 5 3 5 5 3 1 5
## 45704 45711 45714 45716 45718 45720 45723 45727 45730 45737 45739 45742 45746
## 3 5 5 4 3 3 4 5 5 3 3 5 5
## 45752 45755 45757 45758 45759 45761 45762 45769 45783 45784 45792 45794 45799
## 3 5 3 3 3 5 5 3 2 2 2 2 2
## 45801 45803 45805 45808 45810 45811 45832 45835 45837 45845 45847 45851 45856
## 3 2 2 2 2 2 3 5 3 5 5 5 2
## 45858 45865 45870 45872 45879 45881 45886 45894 45897 45899 45908 45912 45915
## 2 3 3 5 2 5 2 5 5 2 4 4 2
## 45917 45919 45923 45924 45925 45928 45933 45935 45940 45945 45950 45952 45962
## 2 2 2 4 4 4 4 2 4 5 3 3 5
## 45967 45969 45972 45973 45974 45975 45976 45980 45981 45983 45991 45993 45996
## 5 3 2 5 2 5 3 3 3 2 2 2 2
## 45997 45998 46001 46003 46009 46010 46011 46019 46027 46028 46034 46036 46039
## 3 3 2 3 2 3 2 5 5 2 3 5 2
## 46040 46041 46044 46045 46047 46053 46064 46065 46068 46070 46083 46084 46086
## 3 3 2 3 3 2 2 2 2 2 2 3 3
## 46090 46092 46097 46101 46108 46109 46113 46114 46116 46117 46121 46123 46127
## 1 3 2 2 1 1 5 3 5 2 3 3 3
## 46128 46135 46140 46146 46147 46149 46154 46157 46159 46162 46165 46171 46175
## 3 3 3 3 3 3 3 2 2 4 5 2 4
## 46180 46181 46182 46186 46187 46195 46198 46200 46203 46207 46208 46209 46210
## 5 5 5 1 5 5 1 1 5 5 2 4 4
## 46211 46212 46214 46218 46221 46225 46226 46231 46238 46240 46244 46248 46250
## 4 1 3 1 2 5 4 5 3 3 3 3 5
## 46254 46256 46258 46259 46263 46264 46265 46266 46267 46272 46273 46275 46277
## 4 5 3 5 5 3 5 5 5 3 3 3 5
## 46278 46280 46290 46298 46300 46301 46311 46315 46317 46319
## 3 3 3 3 3 3 1 1 4 3
##
## Within cluster sum of squares by cluster:
## [1] 71.65958 206.44037 307.73531 145.82141 213.53876
## (between_SS / total_SS = 58.8 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"# Plot of Cluster
fviz_cluster(kmeans_result, data = nor)
# Silhouette coefficient
sil = as.data.frame(silhouette(kmeans_result$cluster, dist(nor)))
mean(sil$sil_width) # 0.26 <- worse than simplistic model## [1] 0.2613641fviz_silhouette(silhouette(kmeans_result$cluster, dist(nor)))## cluster size ave.sil.width
## 1 1 11 0.41
## 2 2 46 0.30
## 3 3 64 0.26
## 4 4 17 0.11
## 5 5 54 0.25
# Adding Clusters to data set
test = test %>%
mutate(km.group = factor(kmeans_result$cluster, labels=c("cl1","cl2", "cl3", "cl4", "cl5")))
# Summarizing the cluster groups
test %>%
group_by(km.group) %>%
summarise(count = n(),
RPL_EJI = mean(RPL_EJI),
EP_MINRTY = mean(EP_MINRTY),
EP_POV200 = mean(EP_POV200),
EP_NOHSDP = mean(EP_NOHSDP),
EP_RENTER = mean(EP_RENTER),
EP_HOUBDN = mean(EP_HOUBDN),
EPL_NOINT = mean(EPL_NOINT),
EP_ASTHMA = mean(EP_ASTHMA),
F_CANCER = mean(F_CANCER),
EP_DIABETES = mean(EP_DIABETES),
F_HVM = mean(F_HVM),
EP_MHLTH = mean(EP_MHLTH))# 6% are in cluster 1 (non-minority)
# 24% are in cluster 2 (minority)
# 33% are in cluster 3 (non-minority)
# 9% are in cluster 4 (minority) (almost always the highest except for cancer)
# 28% are in cluster 5 (minority)